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-rw-r--r--backend/microservice/api/newmlservice.py48
-rw-r--r--frontend/package-lock.json166
-rw-r--r--frontend/src/app/_elements/dataset-load/dataset-load.component.ts100
-rw-r--r--frontend/src/app/_elements/model-load/model-load.component.html215
-rw-r--r--frontend/src/app/_elements/model-load/model-load.component.ts114
5 files changed, 95 insertions, 548 deletions
diff --git a/backend/microservice/api/newmlservice.py b/backend/microservice/api/newmlservice.py
index bca729e4..07735077 100644
--- a/backend/microservice/api/newmlservice.py
+++ b/backend/microservice/api/newmlservice.py
@@ -291,15 +291,16 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
random=123
else:
random=0
- x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=test, random_state=random)
+ #x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=test, random_state=random)
#print(x_train,x_test)
-
+ x, x_test, y, y_test = train_test_split(x, y, test_size=0.15, shuffle=True)
+ x_train, x_val, y_train, y_val = train_test_split(x, y, test_size=0.15, shuffle=True)
#
# Treniranje modela
#
#
###OPTIMIZATORI
-
+ print(paramsModel['optimizer'])
if(paramsModel['optimizer']=='Adam'):
opt=tf.keras.optimizers.Adam(learning_rate=3)
@@ -315,13 +316,16 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
elif(paramsModel['optimizer']=='Nadam'):
opt=tf.keras.optimizers.Nadam(learning_rate=float(paramsModel['learningRate']))
- elif(paramsModel['optimizer']=='Sgd'):
+ elif(paramsModel['optimizer']=='SGD'):
+ opt=tf.keras.optimizers.SGD(learning_rate=float(paramsModel['learningRate']))
+
+ if(paramsModel['optimizer']=='SGDMomentum'):
opt=tf.keras.optimizers.SGD(learning_rate=float(paramsModel['learningRate']))
elif(paramsModel['optimizer']=='Ftrl'):
opt=tf.keras.optimizers.Ftrl(learning_rate=float(paramsModel['learningRate']))
- elif(paramsModel['optimizer']=='Rmsprop'):
+ elif(paramsModel['optimizer']=='RMSprop'):
opt=tf.keras.optimizers.RMSprop(learning_rate=float(paramsModel['learningRate']))
###REGULARIZACIJA
@@ -331,7 +335,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
filepath=os.path.join("temp/",paramsExperiment['_id']+"_"+paramsModel['_id']+".h5")
if(problem_type=='multi-klasifikacioni'):
#print('multi')
- print(paramsModel)
+ #print(paramsModel)
reg=paramsModel['layers'][0]['regularisation']
regRate=float(paramsModel['layers'][0]['regularisationRate'])
if(reg=='l1'):
@@ -367,7 +371,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
classifier.compile(loss =paramsModel["lossFunction"] , optimizer =opt, metrics = ['accuracy','mae','mse'])
- history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']))
+ history=classifier.fit( x=x_train, y=y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']),validation_data=(x_val, y_val))
hist=history.history
#plt.plot(hist['accuracy'])
@@ -380,12 +384,30 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
classifier.save(filepath, save_format='h5')
-
+
+ accuracy=metrics.accuracy_score(y_test, y_pred)
+ macro_averaged_precision=metrics.precision_score(y_test, y_pred, average = 'macro')
+ micro_averaged_precision=metrics.precision_score(y_test, y_pred, average = 'micro')
+ macro_averaged_recall=metrics.recall_score(y_test, y_pred, average = 'macro')
+ micro_averaged_recall=metrics.recall_score(y_test, y_pred, average = 'micro')
+ macro_averaged_f1=metrics.f1_score(y_test, y_pred, average = 'macro')
+ micro_averaged_f1=metrics.f1_score(y_test, y_pred, average = 'micro')
+
+ metrics= {
+ "accuracy" : float(accuracy),
+ "macro_averaged_precision" :float(macro_averaged_precision),
+ "micro_averaged_precision" : float(micro_averaged_precision),
+ "macro_averaged_recall" : float(macro_averaged_recall),
+ "micro_averaged_recall" : float(micro_averaged_recall),
+ "macro_averaged_f1" : float(macro_averaged_f1),
+ "micro_averaged_f1" : float(micro_averaged_f1)
+ }
+
#vizuelizacija u python-u
#from ann_visualizer.visualize import ann_viz;
#ann_viz(classifier, title="My neural network")
- return filepath,hist,y_pred,y_test
+ return filepath,hist,metrics
elif(problem_type=='binarni-klasifikacioni'):
#print('*************************************************************************binarni')
@@ -421,7 +443,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
classifier.compile(loss =paramsModel["lossFunction"] , optimizer =opt , metrics = ['accuracy','mae','mse'])
- history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']))
+ history=classifier.fit( x=x_train, y=y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']),validation_data=(x_val, y_val))
hist=history.history
y_pred=classifier.predict(x_test)
y_pred=(y_pred>=0.5).astype('int')
@@ -491,7 +513,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
classifier.compile(loss =paramsModel["lossFunction"] , optimizer = opt , metrics = ['accuracy','mae','mse'])
- history=classifier.fit(x_train, y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']))
+ history=classifier.fit( x=x_train, y=y_train, epochs = paramsModel['epochs'],batch_size=int(paramsModel['batchSize']),callbacks=callback(x_test, y_test,paramsModel['_id']),validation_data=(x_val, y_val))
hist=history.history
y_pred=classifier.predict(x_test)
#print(classifier.evaluate(x_test, y_test))
@@ -543,7 +565,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
#
# Metrike
#
-
+ '''
if(problem_type=="regresioni"):
# https://www.analyticsvidhya.com/blog/2021/05/know-the-best-evaluation-metrics-for-your-regression-model/
mse = float(sm.mean_squared_error(y_test,y_pred))
@@ -565,7 +587,7 @@ def train(dataset, paramsModel,paramsExperiment,paramsDataset,callback):
"r2" : r2,
"adj_r2" : adj_r2
}
- '''
+
elif(problem_type=="multi-klasifikacioni"):
cr=sm.classification_report(y_test, y_pred)
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
index 9da54c53..ebe30390 100644
--- a/frontend/package-lock.json
+++ b/frontend/package-lock.json
@@ -435,7 +435,6 @@
},
"node_modules/@angular/compiler-cli": {
"version": "13.2.5",
- "dev": true,
"license": "MIT",
"dependencies": {
"@babel/core": "^7.17.2",
@@ -464,7 +463,6 @@
},
"node_modules/@angular/compiler-cli/node_modules/@ampproject/remapping": {
"version": "2.1.2",
- "dev": true,
"license": "Apache-2.0",
"dependencies": {
"@jridgewell/trace-mapping": "^0.3.0"
@@ -475,7 +473,6 @@
},
"node_modules/@angular/compiler-cli/node_modules/@babel/core": {
"version": "7.17.5",
- "dev": true,
"license": "MIT",
"dependencies": {
"@ampproject/remapping": "^2.1.0",
@@ -504,7 +501,6 @@
},
"node_modules/@angular/compiler-cli/node_modules/@babel/core/node_modules/semver": {
"version": "6.3.0",
- "dev": true,
"license": "ISC",
"bin": {
"semver": "bin/semver.js"
@@ -512,7 +508,6 @@
},
"node_modules/@angular/compiler-cli/node_modules/@babel/generator": {
"version": "7.17.3",
- "dev": true,
"license": "MIT",
"dependencies": {
"@babel/types": "^7.17.0",
@@ -525,7 +520,6 @@
},
"node_modules/@angular/compiler-cli/node_modules/source-map": {
"version": "0.5.7",
- "dev": true,
"license": "BSD-3-Clause",
"engines": {
"node": ">=0.10.0"
@@ -748,7 +742,6 @@
},
"node_modules/@babel/core": {
"version": "7.16.12",
- "dev": true,
"license": "MIT",
"dependencies": {
"@babel/code-frame": "^7.16.7",
@@ -777,7 +770,6 @@
},
"node_modules/@babel/core/node_modules/semver": {
"version": "6.3.0",
- "dev": true,
"license": "ISC",
"bin": {
"semver": "bin/semver.js"
@@ -785,7 +777,6 @@
},
"node_modules/@babel/core/node_modules/source-map": {
"version": "0.5.7",
- "dev": true,
"license": "BSD-3-Clause",
"engines": {
"node": ">=0.10.0"
@@ -793,7 +784,6 @@
},
"node_modules/@babel/generator": {
"version": "7.16.8",
- "dev": true,
"license": "MIT",
"dependencies": {
"@babel/types": "^7.16.8",
@@ -806,7 +796,6 @@
},
"node_modules/@babel/generator/node_modules/source-map": {
"version": "0.5.7",
- "dev": true,
"license": "BSD-3-Clause",
"engines": {
"node": ">=0.10.0"
@@ -3254,7 +3243,6 @@
},
"node_modules/anymatch": {
"version": "3.1.2",
- "dev": true,
"license": "ISC",
"dependencies": {
"normalize-path": "^3.0.0",
@@ -3505,7 +3493,6 @@
},
"node_modules/binary-extensions": {
"version": "2.2.0",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">=8"
@@ -3593,7 +3580,6 @@
},
"node_modules/braces": {
"version": "3.0.2",
- "dev": true,
"license": "MIT",
"dependencies": {
"fill-range": "^7.0.1"
@@ -3771,7 +3757,6 @@
},
"node_modules/chokidar": {
"version": "3.5.3",
- "dev": true,
"funding": [
{
"type": "individual",
@@ -4714,7 +4699,6 @@
},
"node_modules/dependency-graph": {
"version": "0.11.0",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">= 0.6.0"
@@ -4861,7 +4845,6 @@
},
"node_modules/encoding": {
"version": "0.1.13",
- "dev": true,
"license": "MIT",
"optional": true,
"dependencies": {
@@ -4870,7 +4853,6 @@
},
"node_modules/encoding/node_modules/iconv-lite": {
"version": "0.6.3",
- "dev": true,
"license": "MIT",
"optional": true,
"dependencies": {
@@ -5346,7 +5328,6 @@
},
"node_modules/fill-range": {
"version": "7.0.1",
- "dev": true,
"license": "MIT",
"dependencies": {
"to-regex-range": "^5.0.1"
@@ -5595,7 +5576,6 @@
},
"node_modules/glob-parent": {
"version": "5.1.2",
- "dev": true,
"license": "ISC",
"dependencies": {
"is-glob": "^4.0.1"
@@ -6133,7 +6113,6 @@
},
"node_modules/is-binary-path": {
"version": "2.1.0",
- "dev": true,
"license": "MIT",
"dependencies": {
"binary-extensions": "^2.0.0"
@@ -6183,7 +6162,6 @@
},
"node_modules/is-extglob": {
"version": "2.1.1",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">=0.10.0"
@@ -6198,7 +6176,6 @@
},
"node_modules/is-glob": {
"version": "4.0.3",
- "dev": true,
"license": "MIT",
"dependencies": {
"is-extglob": "^2.1.1"
@@ -6222,7 +6199,6 @@
},
"node_modules/is-number": {
"version": "7.0.0",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">=0.12.0"
@@ -7011,7 +6987,6 @@
},
"node_modules/lru-cache": {
"version": "6.0.0",
- "dev": true,
"license": "ISC",
"dependencies": {
"yallist": "^4.0.0"
@@ -7022,7 +6997,6 @@
},
"node_modules/magic-string": {
"version": "0.25.7",
- "dev": true,
"license": "MIT",
"dependencies": {
"sourcemap-codec": "^1.4.4"
@@ -7565,7 +7539,6 @@
},
"node_modules/normalize-path": {
"version": "3.0.0",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">=0.10.0"
@@ -8202,7 +8175,6 @@
},
"node_modules/picomatch": {
"version": "2.3.1",
- "dev": true,
"license": "MIT",
"engines": {
"node": ">=8.6"
@@ -8953,7 +8925,6 @@
},
"node_modules/readdirp": {
"version": "3.6.0",
- "dev": true,
"license": "MIT",
"dependencies": {
"picomatch": "^2.2.1"
@@ -9228,7 +9199,7 @@
},
"node_modules/safer-buffer": {
"version": "2.1.2",
- "dev": true,
+ "devOptional": true,
"license": "MIT"
},
"node_modules/sass": {
@@ -9348,7 +9319,6 @@
},
"node_modules/semver": {
"version": "7.3.5",
- "dev": true,
"license": "ISC",
"dependencies": {
"lru-cache": "^6.0.0"
@@ -9698,7 +9668,6 @@
},
"node_modules/sourcemap-codec": {
"version": "1.4.8",
- "dev": true,
"license": "MIT"
},
"node_modules/spdy": {
@@ -10077,7 +10046,6 @@
},
"node_modules/to-regex-range": {
"version": "5.0.1",
- "dev": true,
"license": "MIT",
"dependencies": {
"is-number": "^7.0.0"
@@ -10159,7 +10127,6 @@
},
"node_modules/typescript": {
"version": "4.5.5",
- "dev": true,
"license": "Apache-2.0",
"bin": {
"tsc": "bin/tsc",
@@ -10781,7 +10748,6 @@
},
"node_modules/yallist": {
"version": "4.0.0",
- "dev": true,
"license": "ISC"
},
"node_modules/yaml": {
@@ -11067,7 +11033,6 @@
},
"@angular/compiler-cli": {
"version": "13.2.5",
- "dev": true,
"requires": {
"@babel/core": "^7.17.2",
"chokidar": "^3.0.0",
@@ -11083,14 +11048,12 @@
"dependencies": {
"@ampproject/remapping": {
"version": "2.1.2",
- "dev": true,
"requires": {
"@jridgewell/trace-mapping": "^0.3.0"
}
},
"@babel/core": {
"version": "7.17.5",
- "dev": true,
"requires": {
"@ampproject/remapping": "^2.1.0",
"@babel/code-frame": "^7.16.7",
@@ -11110,14 +11073,12 @@
},
"dependencies": {
"semver": {
- "version": "6.3.0",
- "dev": true
+ "version": "6.3.0"
}
}
},
"@babel/generator": {
"version": "7.17.3",
- "dev": true,
"requires": {
"@babel/types": "^7.17.0",
"jsesc": "^2.5.1",
@@ -11125,8 +11086,7 @@
}
},
"source-map": {
- "version": "0.5.7",
- "dev": true
+ "version": "0.5.7"
}
}
},
@@ -11237,7 +11197,6 @@
},
"@babel/core": {
"version": "7.16.12",
- "dev": true,
"requires": {
"@babel/code-frame": "^7.16.7",
"@babel/generator": "^7.16.8",
@@ -11257,18 +11216,15 @@
},
"dependencies": {
"semver": {
- "version": "6.3.0",
- "dev": true
+ "version": "6.3.0"
},
"source-map": {
- "version": "0.5.7",
- "dev": true
+ "version": "0.5.7"
}
}
},
"@babel/generator": {
"version": "7.16.8",
- "dev": true,
"requires": {
"@babel/types": "^7.16.8",
"jsesc": "^2.5.1",
@@ -11276,8 +11232,7 @@
},
"dependencies": {
"source-map": {
- "version": "0.5.7",
- "dev": true
+ "version": "0.5.7"
}
}
},
@@ -12210,7 +12165,8 @@
},
"dependencies": {
"ws": {
- "version": "7.5.7"
+ "version": "7.5.7",
+ "requires": {}
}
}
},
@@ -12222,7 +12178,8 @@
},
"@ngtools/webpack": {
"version": "13.2.5",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"@nodelib/fs.scandir": {
"version": "2.1.5",
@@ -12774,7 +12731,8 @@
},
"acorn-import-assertions": {
"version": "1.8.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"adjust-sourcemap-loader": {
"version": "4.0.0",
@@ -12872,7 +12830,6 @@
},
"anymatch": {
"version": "3.1.2",
- "dev": true,
"requires": {
"normalize-path": "^3.0.0",
"picomatch": "^2.0.4"
@@ -13024,8 +12981,7 @@
"dev": true
},
"binary-extensions": {
- "version": "2.2.0",
- "dev": true
+ "version": "2.2.0"
},
"bl": {
"version": "4.1.0",
@@ -13082,7 +13038,8 @@
"dev": true
},
"bootstrap": {
- "version": "5.1.3"
+ "version": "5.1.3",
+ "requires": {}
},
"brace-expansion": {
"version": "1.1.11",
@@ -13093,7 +13050,6 @@
},
"braces": {
"version": "3.0.2",
- "dev": true,
"requires": {
"fill-range": "^7.0.1"
}
@@ -13202,7 +13158,6 @@
},
"chokidar": {
"version": "3.5.3",
- "dev": true,
"requires": {
"anymatch": "~3.1.2",
"braces": "~3.0.2",
@@ -13224,7 +13179,8 @@
},
"circular-dependency-plugin": {
"version": "5.2.2",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"clean-stack": {
"version": "2.2.0",
@@ -13595,7 +13551,8 @@
},
"css-prefers-color-scheme": {
"version": "6.0.3",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"css-select": {
"version": "4.2.1",
@@ -13795,8 +13752,7 @@
"dev": true
},
"dependency-graph": {
- "version": "0.11.0",
- "dev": true
+ "version": "0.11.0"
},
"destroy": {
"version": "1.0.4",
@@ -13895,7 +13851,6 @@
},
"encoding": {
"version": "0.1.13",
- "dev": true,
"optional": true,
"requires": {
"iconv-lite": "^0.6.2"
@@ -13903,7 +13858,6 @@
"dependencies": {
"iconv-lite": {
"version": "0.6.3",
- "dev": true,
"optional": true,
"requires": {
"safer-buffer": ">= 2.1.2 < 3.0.0"
@@ -14216,7 +14170,6 @@
},
"fill-range": {
"version": "7.0.1",
- "dev": true,
"requires": {
"to-regex-range": "^5.0.1"
}
@@ -14365,7 +14318,6 @@
},
"glob-parent": {
"version": "5.1.2",
- "dev": true,
"requires": {
"is-glob": "^4.0.1"
}
@@ -14562,7 +14514,8 @@
},
"icss-utils": {
"version": "5.1.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"ieee754": {
"version": "1.2.1",
@@ -14709,7 +14662,6 @@
},
"is-binary-path": {
"version": "2.1.0",
- "dev": true,
"requires": {
"binary-extensions": "^2.0.0"
}
@@ -14733,15 +14685,13 @@
"dev": true
},
"is-extglob": {
- "version": "2.1.1",
- "dev": true
+ "version": "2.1.1"
},
"is-fullwidth-code-point": {
"version": "3.0.0"
},
"is-glob": {
"version": "4.0.3",
- "dev": true,
"requires": {
"is-extglob": "^2.1.1"
}
@@ -14755,8 +14705,7 @@
"dev": true
},
"is-number": {
- "version": "7.0.0",
- "dev": true
+ "version": "7.0.0"
},
"is-path-cwd": {
"version": "2.2.0",
@@ -15080,7 +15029,8 @@
},
"karma-jasmine-html-reporter": {
"version": "1.7.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"karma-source-map-support": {
"version": "1.4.0",
@@ -15248,14 +15198,12 @@
},
"lru-cache": {
"version": "6.0.0",
- "dev": true,
"requires": {
"yallist": "^4.0.0"
}
},
"magic-string": {
"version": "0.25.7",
- "dev": true,
"requires": {
"sourcemap-codec": "^1.4.4"
}
@@ -15590,8 +15538,7 @@
}
},
"normalize-path": {
- "version": "3.0.0",
- "dev": true
+ "version": "3.0.0"
},
"normalize-range": {
"version": "0.1.2",
@@ -16006,8 +15953,7 @@
"version": "1.0.0"
},
"picomatch": {
- "version": "2.3.1",
- "dev": true
+ "version": "2.3.1"
},
"pify": {
"version": "2.3.0",
@@ -16097,7 +16043,8 @@
},
"postcss-custom-media": {
"version": "8.0.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-custom-properties": {
"version": "12.1.4",
@@ -16151,11 +16098,13 @@
},
"postcss-font-variant": {
"version": "5.0.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-gap-properties": {
"version": "3.0.3",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-image-set-function": {
"version": "4.0.6",
@@ -16175,7 +16124,8 @@
},
"postcss-initial": {
"version": "4.0.1",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-lab-function": {
"version": "4.1.1",
@@ -16196,15 +16146,18 @@
},
"postcss-logical": {
"version": "5.0.4",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-media-minmax": {
"version": "5.0.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-modules-extract-imports": {
"version": "3.0.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-modules-local-by-default": {
"version": "4.0.0",
@@ -16238,11 +16191,13 @@
},
"postcss-overflow-shorthand": {
"version": "3.0.3",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-page-break": {
"version": "3.0.4",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-place": {
"version": "7.0.4",
@@ -16299,7 +16254,8 @@
},
"postcss-replace-overflow-wrap": {
"version": "4.0.0",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"postcss-selector-not": {
"version": "5.0.0",
@@ -16427,7 +16383,6 @@
},
"readdirp": {
"version": "3.6.0",
- "dev": true,
"requires": {
"picomatch": "^2.2.1"
}
@@ -16599,7 +16554,7 @@
},
"safer-buffer": {
"version": "2.1.2",
- "dev": true
+ "devOptional": true
},
"sass": {
"version": "1.49.0",
@@ -16643,7 +16598,8 @@
},
"ajv-keywords": {
"version": "3.5.2",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"json-schema-traverse": {
"version": "0.4.1",
@@ -16664,7 +16620,6 @@
},
"semver": {
"version": "7.3.5",
- "dev": true,
"requires": {
"lru-cache": "^6.0.0"
}
@@ -16910,8 +16865,7 @@
}
},
"sourcemap-codec": {
- "version": "1.4.8",
- "dev": true
+ "version": "1.4.8"
},
"spdy": {
"version": "4.0.2",
@@ -17081,7 +17035,8 @@
},
"ajv-keywords": {
"version": "3.5.2",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"json-schema-traverse": {
"version": "0.4.1",
@@ -17135,7 +17090,6 @@
},
"to-regex-range": {
"version": "5.0.1",
- "dev": true,
"requires": {
"is-number": "^7.0.0"
}
@@ -17184,8 +17138,7 @@
"dev": true
},
"typescript": {
- "version": "4.5.5",
- "dev": true
+ "version": "4.5.5"
},
"ua-parser-js": {
"version": "0.7.31",
@@ -17344,7 +17297,8 @@
},
"ajv-keywords": {
"version": "3.5.2",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"json-schema-traverse": {
"version": "0.4.1",
@@ -17538,7 +17492,8 @@
},
"ws": {
"version": "8.2.3",
- "dev": true
+ "dev": true,
+ "requires": {}
},
"xlsx": {
"version": "0.18.5",
@@ -17556,8 +17511,7 @@
"version": "5.0.8"
},
"yallist": {
- "version": "4.0.0",
- "dev": true
+ "version": "4.0.0"
},
"yaml": {
"version": "1.10.2",
diff --git a/frontend/src/app/_elements/dataset-load/dataset-load.component.ts b/frontend/src/app/_elements/dataset-load/dataset-load.component.ts
deleted file mode 100644
index 73dbf2d2..00000000
--- a/frontend/src/app/_elements/dataset-load/dataset-load.component.ts
+++ /dev/null
@@ -1,100 +0,0 @@
-import { Component, OnInit, ViewChild, ViewChildren } from '@angular/core';
-import { AddNewDatasetComponent } from '../add-new-dataset/add-new-dataset.component';
-import { ModelsService } from 'src/app/_services/models.service';
-import shared from 'src/app/Shared';
-import Dataset from 'src/app/_data/Dataset';
-import { DatatableComponent, TableData } from 'src/app/_elements/datatable/datatable.component';
-import { DatasetsService } from 'src/app/_services/datasets.service';
-import { CsvParseService } from 'src/app/_services/csv-parse.service';
-import { Output, EventEmitter } from '@angular/core';
-import { SignalRService } from 'src/app/_services/signal-r.service';
-
-@Component({
- selector: 'app-dataset-load',
- templateUrl: './dataset-load.component.html',
- styleUrls: ['./dataset-load.component.css']
-})
-export class DatasetLoadComponent implements OnInit {
-
- @Output() selectedDatasetChangeEvent = new EventEmitter<Dataset>();
-
- @ViewChild(AddNewDatasetComponent) addNewDatasetComponent!: AddNewDatasetComponent;
- @ViewChild(AddNewDatasetComponent) datatable!: DatatableComponent;
-
- datasetLoaded: boolean = false;
- selectedDatasetLoaded: boolean = false;
-
- showMyDatasets: boolean = true;
- myDatasets?: Dataset[];
- existingDatasetSelected: boolean = false;
- selectedDataset?: Dataset;
-
- tableData: TableData = new TableData();
-
- term: string = "";
-
- constructor(private models: ModelsService, private datasets: DatasetsService, private csv: CsvParseService, private signalRService: SignalRService) {
- this.datasets.getMyDatasets().subscribe((datasets) => {
- this.myDatasets = datasets;
- });
- }
-
- viewMyDatasetsForm() {
- this.showMyDatasets = true;
- if (this.selectedDataset != undefined)
- this.resetSelectedDataset();
- //this.resetCbsAndRbs(); //TREBA DA SE DESI
- }
- viewNewDatasetForm() {
- this.showMyDatasets = false;
- if (this.selectedDataset != undefined)
- this.resetSelectedDataset();
- //this.resetCbsAndRbs(); //TREBA DA SE DESI
- }
-
- refreshMyDatasets() {
- this.datasets.getMyDatasets().subscribe((datasets) => {
- this.myDatasets = datasets;
- this.showMyDatasets = true;
- });
- }
-
- selectThisDataset(dataset: Dataset) {
- this.selectedDataset = dataset;
- this.selectedDatasetLoaded = false;
- this.existingDatasetSelected = true;
- this.tableData.hasHeader = this.selectedDataset.hasHeader;
-
- this.tableData.hasInput = true;
- this.tableData.loaded = false;
-
- this.datasets.getDatasetFile(dataset.fileId).subscribe((file: string | undefined) => {
- if (file) {
- this.tableData.loaded = true;
- this.tableData.numRows = this.selectedDataset!.rowCount;
- this.tableData.numCols = this.selectedDataset!.columnInfo.length;
- this.tableData.data = this.csv.csvToArray(file, (dataset.delimiter == "razmak") ? " " : (dataset.delimiter == "") ? "," : dataset.delimiter);
- //this.resetCbsAndRbs(); //TREBA DA SE DESI
- //this.refreshThreeNullValueRadioOptions(); //TREBA DA SE DESI
- this.selectedDatasetLoaded = true;
-
- this.selectedDatasetChangeEvent.emit(this.selectedDataset);
- }
- });
- }
-
- resetSelectedDataset(): boolean {
- this.selectedDatasetChangeEvent.emit(this.selectedDataset);
- return true;
- }
-
- ngOnInit(): void {
- if (this.signalRService.hubConnection) {
- this.signalRService.hubConnection.on("NotifyDataset", _ => {
- this.refreshMyDatasets();
- });
- } else {
- console.warn("Dataset-Load: No connection!");
- }
- }
-}
diff --git a/frontend/src/app/_elements/model-load/model-load.component.html b/frontend/src/app/_elements/model-load/model-load.component.html
deleted file mode 100644
index dcb35c21..00000000
--- a/frontend/src/app/_elements/model-load/model-load.component.html
+++ /dev/null
@@ -1,215 +0,0 @@
-<div>
- <div class="d-flex flex-row justify-content-center align-items-center mt-3 mb-5">
- <button type="button" id="btnMyModel" class="btn" (click)="viewMyModelsForm()"
- [ngClass]="{'btnType1': showMyModels, 'btnType2': !showMyModels}">
- Izaberite model iz kolekcije
- </button>
- <h3 class="mt-3 mx-3">ili</h3>
- <button type="button" id="btnNewModel" class="btn" (click)="viewNewModelForm()"
- [ngClass]="{'btnType1': !showMyModels, 'btnType2': showMyModels}">
- Dodajte novi model
- </button>
- </div>
-
- <div *ngIf="showMyModels" class="px-5 my-3">
- <input *ngIf="showMyModels" type="text" class="form-control" placeholder="Pretraga" [(ngModel)]="term">
- </div>
- <div *ngIf="showMyModels" class="px-5">
- <div class="overflow-auto" style="max-height: 500px;">
- <ul class="list-group">
- <li class="list-group-item p-3" *ngFor="let model of myModels|filter:term|filter:(forExperiment ? forExperiment.type : '')"
- [ngClass]="{'selectedModelClass': this.selectedModel == model}">
- <app-item-model name="usersModel" [model]="model" (click)="selectThisModel(model);">
- </app-item-model>
- </li>
- </ul>
- <div class="px-5 mt-5">
- <!--prikaz izabranog modela-->
- </div>
- </div>
- </div>
-
-
- <div *ngIf="!showMyModels">
- <div class="form-group row mt-3 mb-2 d-flex justify-content-center">
-
- <div class="col-3">
- <label for="name" class="col-form-label">Naziv modela:</label>
- <input type="text" class="form-control" name="name" placeholder="Naziv..." [(ngModel)]="newModel.name">
- </div>
- <div class="col-5">
- <label for="desc" class="col-sm-2 col-form-label">Opis:</label>
- <div>
- <textarea class="form-control" name="desc" rows="3" [(ngModel)]="newModel.description"></textarea>
- </div>
- </div>
-
- </div>
- <h2 class="mt-5 mb-4 mx-5">Parametri treniranja modela:</h2>
- <div>
-
- <div class="row p-2">
- <div class="col-1"></div>
- <div class="col-3">
- <label for="type" class="col-form-label">Tip problema: </label>
- </div>
- <div class="col-2">
- <select id=typeOptions class="form-select" name="type" [(ngModel)]="newModel.type"
- (change)="filterOptions()">
- <option
- *ngFor="let option of Object.keys(ProblemType); let optionName of Object.values(ProblemType)"
- [value]="option">
- {{ optionName }}
- </option>
- </select>
- </div>
- <div class="col-1"></div>
- <div class="col-3">
- <label for="hiddenLayers" class="col-form-label">Broj skrivenih slojeva: </label>
- </div>
- <div class="col-1">
- <input type="number" min="1" class="form-control" name="hiddenLayers"
- [(ngModel)]="newModel.hiddenLayers"
- (change)="newModel.hiddenLayerActivationFunctions = [].constructor(newModel.hiddenLayers).fill(newModel.hiddenLayerActivationFunctions[0])"
- (ngModelChange)="updateGraph()">
- </div>
- </div>
-
- <div class="row p-2">
- <div class="col-1">
- </div>
- <div class="col-3">
- <label for="optimizer" class="col-form-label">Optimizacija: </label>
- </div>
- <div class="col-2">
- <select id=optimizerOptions class="form-select" name="optimizer" [(ngModel)]="newModel.optimizer">
- <option
- *ngFor="let option of Object.keys(Optimizer); let optionName of Object.values(Optimizer)"
- [value]="option">
- {{ optionName }}
- </option>
- </select>
- </div>
- <div class="col-1">
- </div>
- <div class="col-3">
- <label for="hiddenLayerNeurons" class="col-form-label">Broj neurona skrivenih slojeva: </label>
- </div>
- <div class="col-1">
- <input type="number" min="1" class="form-control" name="hiddenLayerNeurons"
- [(ngModel)]="newModel.hiddenLayerNeurons" (ngModelChange)="updateGraph()">
- </div>
- </div>
-
- <div class="row p-2">
- <div class="col-1"></div>
- <div class="col-3">
- <label for="lossFunction" class="col-form-label">Funkcija troška: </label>
- </div>
- <div class="col-2">
- <select id=lossFunctionOptions class="form-select" name="lossFunction"
- [(ngModel)]="newModel.lossFunction" aria-checked="true">
- <option
- *ngFor="let option of Object.keys(lossFunction); let optionName of Object.values(lossFunction)"
- [value]="option">
- {{ optionName }}
- </option>
- </select>
- </div>
- <div class="col-1"></div>
- <div class="col-3">
- <label for="batchSize" class="col-form-label">Broj uzorka po iteraciji: </label>
- </div>
- <div class="col-1">
-
- <input type="number" min="0" step="1" max="7" class="form-control" name="batchSizePower" [(ngModel)]="batchSizePower" (click)="updateBatchSize()" >
- {{newModel.batchSize}}
-
- </div>
-
- <div class="row p-2">
- <div class="col-1"></div>
- <div class="col-3 m-1">
- <label for="epochs" class="col-form-label">Broj epoha: </label>
- </div>
- <div class="col-1">
- <input type="number" min="1" max="1000" class="form-control" name="epochs"
- [(ngModel)]="newModel.epochs">
- </div>
- </div>
- </div>
-
- <div class="m-5">
- <app-graph [model]="newModel" [inputCols]="1"></app-graph>
- </div>
-
- <h3 class="mx-5 mt-4">Aktivacione funkcije:</h3>
-
- <div class="row p-2" style="align-self: center;">
- <div class="col-1"></div>
- <div class="col-3">
- <label for="hiddenLayerActivationFunction" class="col-form-label"
- style="text-align: center;">Funkcija aktivacije<br>skrivenih slojeva:</label>
- </div>
- <div class="col-2 mt-2">
- <div *ngFor="let item of [].constructor(newModel.hiddenLayers); let i = index">
- <div class="input-group mb-2">
- <div class="input-group-prepend">
- <span class="input-group-text">#{{i+1}}</span>
- </div>
- <select [id]="'hiddenLayerActivationFunctionOption_'+i" class="form-select"
- [(ngModel)]="newModel.hiddenLayerActivationFunctions[i]" >
- <option
- *ngFor="let option of Object.keys(ActivationFunction); let optionName of Object.values(ActivationFunction)"
- [value]="option">
- {{ optionName }}
- </option>
- </select>
- </div>
- </div>
- </div>
- <div class="col-1"></div>
- <div class="col-2">
- <label for="outputLayerActivationFunction" class="col-form-label"
- style="text-align: center;">Funkcija aktivacije<br>izlaznog sloja:</label>
- </div>
- <div class="col-2 mt-2">
- <select id=outputLayerActivationFunctionOptions class="form-select"
- name="outputLayerActivationFunction" [(ngModel)]="newModel.outputLayerActivationFunction">
- <option
- *ngFor="let option of Object.keys(ActivationFunction); let optionName of Object.values(ActivationFunction)"
- [value]="option">
- {{ optionName }}
- </option>
- </select>
- </div>
- <div class="col">
- </div>
- </div>
- </div>
-
- <div class="form-check form-check-inline overflow-auto m-4" style="width: max-content;">
- <h3>Izaberite metrike:</h3>
- <div id="divMetricsinput" class="mt-2 mx-5">
-
- <div *ngFor="let option of Object.keys(metrics); let optionName of Object.values(metrics) "
- class="form-check form-check-inline">
-
- <input name="cbmetrics" class="form-check-input" type="checkbox" value="{{option}}"
- id="metrics_{{option}}" style="float: left;" checked>
- <label class="form-check-label" for="metrics_{{option}}" for="inlineCheckbox2">
- {{optionName}}
- </label>
- </div>
- </div>
- </div>
-
- <div class="form-group row mt-3 mb-3">
- <div class="col"></div>
- <button class="btn btn-lg col-4" style="background-color:#003459; color:white;"
- (click)="uploadModel();">Sačuvaj
- model</button>
- <div class="col"></div>
- </div>
- </div>
-</div> \ No newline at end of file
diff --git a/frontend/src/app/_elements/model-load/model-load.component.ts b/frontend/src/app/_elements/model-load/model-load.component.ts
deleted file mode 100644
index dbca3d17..00000000
--- a/frontend/src/app/_elements/model-load/model-load.component.ts
+++ /dev/null
@@ -1,114 +0,0 @@
-import { Component, OnInit, ViewChild, Output, EventEmitter, Input } from '@angular/core';
-import Shared from 'src/app/Shared';
-import Experiment from 'src/app/_data/Experiment';
-import Model, { ActivationFunction, LossFunction, LossFunctionBinaryClassification, LossFunctionMultiClassification, LossFunctionRegression, Metrics, MetricsBinaryClassification, MetricsMultiClassification, MetricsRegression, NullValueOptions, Optimizer, ProblemType } from 'src/app/_data/Model';
-import { ModelsService } from 'src/app/_services/models.service';
-import { GraphComponent } from '../graph/graph.component';
-
-
-@Component({
- selector: 'app-model-load',
- templateUrl: './model-load.component.html',
- styleUrls: ['./model-load.component.css']
-})
-export class ModelLoadComponent implements OnInit {
-
- @ViewChild(GraphComponent) graph!: GraphComponent;
- @Input() forExperiment?:Experiment;
- @Output() selectedModelChangeEvent = new EventEmitter<Model>();
-
- newModel: Model = new Model();
- myModels?: Model[];
- selectedModel?: Model;
-
- ProblemType = ProblemType;
- ActivationFunction = ActivationFunction;
- metrics: any = Metrics;
- LossFunction = LossFunction;
- Optimizer = Optimizer;
- Object = Object;
- document = document;
- shared = Shared;
-
- term: string = "";
- selectedProblemType: string = '';
- selectedMetrics = [];
- lossFunction: any = LossFunction;
-
- showMyModels: boolean = true;
-
- constructor(private modelsService: ModelsService) {
- this.modelsService.getMyModels().subscribe((models) => {
- this.myModels = models;
- });
- }
-
- ngOnInit(): void {
- }
- batchSizePower:number=1;
- updateBatchSize()
- {
- this.newModel.batchSize=2**this.batchSizePower;
- }
-
- updateGraph() {
- this.graph.update();
- }
-
- getMetrics() {
- this.newModel.metrics = [];
- let cb = document.getElementsByName("cbmetrics");
-
- for (let i = 0; i < cb.length; i++) {
- let chb = <HTMLInputElement>cb[i];
- if (chb.checked == true)
- this.newModel.metrics.push(chb.value);
- }
- }
-
- uploadModel() {
- this.getMetrics();
-
- this.newModel.uploaderId = Shared.userId;
-
- this.modelsService.addModel(this.newModel).subscribe((response) => {
- Shared.openDialog('Model dodat', 'Model je uspešno dodat u bazu.');
- // treba da se selektuje nov model u listi modela
- //this.selectedModel =
- }, (error) => {
- Shared.openDialog('Greška', 'Model sa unetim nazivom već postoji u Vašoj kolekciji. Promenite naziv modela i nastavite sa kreiranim datasetom.');
- });
- }
-
- filterOptions() {
- switch (this.newModel.type) {
- case 'regresioni':
- this.lossFunction = LossFunctionRegression;
- this.metrics = MetricsRegression;
- break;
- case 'binarni-klasifikacioni':
- this.lossFunction = LossFunctionBinaryClassification;
- this.metrics = MetricsBinaryClassification;
- break;
- case 'multi-klasifikacioni':
- this.lossFunction = LossFunctionMultiClassification;
- this.metrics = MetricsMultiClassification;
- break;
- default:
- break;
- }
- }
-
- viewMyModelsForm() {
- this.showMyModels = true;
- }
- viewNewModelForm() {
- this.showMyModels = false;
- }
-
- selectThisModel(model: Model) {
- this.selectedModel = model;
- this.selectedModelChangeEvent.emit(this.selectedModel);
- }
-
-}
generated by cgit v1.2.3 (git 2.39.1) at 2025-04-20 00:52:37 +0000