diff options
Diffstat (limited to 'frontend/src/app/_data')
| -rw-r--r-- | frontend/src/app/_data/Dataset.ts | 37 | ||||
| -rw-r--r-- | frontend/src/app/_data/Experiment.ts | 27 | ||||
| -rw-r--r-- | frontend/src/app/_data/FolderFile.ts | 14 | ||||
| -rw-r--r-- | frontend/src/app/_data/Model.ts | 82 |
4 files changed, 125 insertions, 35 deletions
diff --git a/frontend/src/app/_data/Dataset.ts b/frontend/src/app/_data/Dataset.ts index 766040a3..4ff0a471 100644 --- a/frontend/src/app/_data/Dataset.ts +++ b/frontend/src/app/_data/Dataset.ts @@ -1,25 +1,27 @@ -export default class Dataset { +import { FolderFile } from "./FolderFile"; + +export default class Dataset extends FolderFile { _id: string = ''; constructor( - public name: string = 'Novi izvor podataka', + name: string = 'Novi izvor podataka', public description: string = '', - public header: string[] = [], public fileId?: number, public extension: string = '.csv', public isPublic: boolean = false, public accessibleByLink: boolean = false, - public dateCreated: Date = new Date(), - public lastUpdated: Date = new Date(), + dateCreated: Date = new Date(), + lastUpdated: Date = new Date(), public uploaderId: string = '', - public delimiter: string = '', - public hasHeader: boolean = true, + public delimiter: string = ',', public columnInfo: ColumnInfo[] = [], public rowCount: number = 0, public nullRows: number = 0, public nullCols: number = 0, - public preview: string[][] = [[]] - ) { } + public cMatrix: number[][] = [] + ) { + super(name, dateCreated, lastUpdated); + } } export class ColumnInfo { @@ -28,9 +30,20 @@ export class ColumnInfo { public isNumber: boolean = false, public numNulls: number = 0, public uniqueValues?: string[], + public uniqueValuesCount?: number[], + public uniqueValuesPercent?: number[], public median?: number, public mean?: number, public min?: number, - public max?: number - ) { } -}
\ No newline at end of file + public max?: number, + public q1?: number, + public q3?: number, + ) { + /*if (isNumber) + this.columnType = ColumnType.numerical; + else + this.columnType = ColumnType.categorical;*/ + } + +} + diff --git a/frontend/src/app/_data/Experiment.ts b/frontend/src/app/_data/Experiment.ts index 95ef6e1e..cff77535 100644 --- a/frontend/src/app/_data/Experiment.ts +++ b/frontend/src/app/_data/Experiment.ts @@ -5,6 +5,7 @@ export default class Experiment { constructor( public name: string = 'Novi eksperiment', public description: string = '', + public type: ProblemType = ProblemType.Regression, public datasetId: string = '', public inputColumns: string[] = [], public outputColumn: string = '', @@ -13,15 +14,11 @@ export default class Experiment { public dateCreated: Date = new Date(), public lastUpdated: Date = new Date(), public modelIds: string[] = [], - - // Test set settings - public randomOrder: boolean = true, - public randomTestSet: boolean = true, - public randomTestSetDistribution: number = 0.1, //0.1-0.9 (10% - 90%) JESTE OVDE ZAKUCANO 10, AL POSLATO JE KAO 0.1 BACK-U - - public encodings: ColumnEncoding[] = [], - public type: ProblemType = ProblemType.Regression + public columnTypes: ColumnType[] = [], + public encodings: ColumnEncoding[] = []//[{columnName: "", columnEncoding: Encoding.Label}] ) { } + + _columnsSelected: boolean = false; } export enum NullValueOptions { @@ -47,11 +44,11 @@ export class NullValReplacer { export enum Encoding { Label = 'label', OneHot = 'onehot', - Ordinal = 'ordinal', + /*Ordinal = 'ordinal', Hashing = 'hashing', Binary = 'binary', BaseN = 'baseN' - /* + BackwardDifference = 'backward difference', CatBoost = 'cat boost', Count = 'count', @@ -69,9 +66,13 @@ export enum Encoding { } export class ColumnEncoding { - constructor ( + constructor( public columnName: string, public encoding: Encoding - ) - {} + ) { } +} + +export enum ColumnType { + categorical = "categorical", + numerical = "numerical" }
\ No newline at end of file diff --git a/frontend/src/app/_data/FolderFile.ts b/frontend/src/app/_data/FolderFile.ts new file mode 100644 index 00000000..c228f25e --- /dev/null +++ b/frontend/src/app/_data/FolderFile.ts @@ -0,0 +1,14 @@ +export class FolderFile { + constructor( + public name: string, + public dateCreated: Date, + public lastUpdated: Date + ) { } +} + + +export enum FolderType { + Dataset, + Model, + Experiment +}
\ No newline at end of file diff --git a/frontend/src/app/_data/Model.ts b/frontend/src/app/_data/Model.ts index 7d383584..526a8290 100644 --- a/frontend/src/app/_data/Model.ts +++ b/frontend/src/app/_data/Model.ts @@ -1,12 +1,13 @@ import { NgIf } from "@angular/common"; +import { FolderFile } from "./FolderFile"; -export default class Model { +export default class Model extends FolderFile { _id: string = ''; constructor( - public name: string = 'Novi model', + name: string = 'Novi model', public description: string = '', - public dateCreated: Date = new Date(), - public lastUpdated: Date = new Date(), + dateCreated: Date = new Date(), + lastUpdated: Date = new Date(), //public experimentId: string = '', // Neural net training settings @@ -14,17 +15,65 @@ export default class Model { public optimizer: Optimizer = Optimizer.Adam, public lossFunction: LossFunction = LossFunction.MeanSquaredError, public inputNeurons: number = 1, - public hiddenLayerNeurons: number = 1, public hiddenLayers: number = 1, - public batchSize: number = 4, - public hiddenLayerActivationFunctions: string[] = ['sigmoid'], + public batchSize: BatchSize = BatchSize.O3, public outputLayerActivationFunction: ActivationFunction = ActivationFunction.Sigmoid, public uploaderId: string = '', public metrics: string[] = [], // TODO add to add-model form - public epochs: number = 5 // TODO add to add-model form + public epochs: number = 5, // TODO add to add-model form + public inputColNum: number = 5, + public learningRate: LearningRate = LearningRate.LR1, + public layers: Layer[] = [new Layer()], + + // Test set settings + public randomOrder: boolean = true, + public randomTestSet: boolean = true, + public randomTestSetDistribution: number = 0.1, //0.1-0.9 (10% - 90%) JESTE OVDE ZAKUCANO 10, AL POSLATO JE KAO 0.1 BACK-U + + public isPublic: boolean = false, + public accessibleByLink: boolean = false + ) { + super(name, dateCreated, lastUpdated); + } +} +export class Layer { + constructor( + public layerNumber: number = 0, + public activationFunction: ActivationFunction = ActivationFunction.Sigmoid, + public neurons: number = 3, + public regularisation: Regularisation = Regularisation.L1, + public regularisationRate: RegularisationRate = RegularisationRate.RR1, ) { } } - +export enum LearningRate { + LR1 = '0.00001', + LR2 = '0.0001', + LR3 = '0.001', + LR4 = '0.003', + LR5 = '0.01', + LR6 = '0.03', + LR7 = '0.1', + LR8 = '0.3', + LR9 = '1', + LR10 = '3', + LR11 = '10', +} +export enum Regularisation { + L1 = 'l1', + L2 = 'l2' +} +export enum RegularisationRate { + RR1 = '0', + RR2 = '0.001', + RR3 = '0.003', + RR4 = '0.01', + RR5 = '0.03', + RR6 = '0.1', + RR7 = '0.3', + RR8 = '1', + RR9 = '3', + RR10 = '10', +} export enum ProblemType { Regression = 'regresioni', BinaryClassification = 'binarni-klasifikacioni', @@ -94,7 +143,7 @@ export enum LossFunctionBinaryClassification { HingeLoss = 'hinge_loss', } export enum LossFunctionMultiClassification { - //CategoricalCrossEntropy = 'categorical_crossentropy', + CategoricalCrossEntropy = 'categorical_crossentropy', SparseCategoricalCrossEntropy = 'sparse_categorical_crossentropy', KLDivergence = 'kullback_leibler_divergence', } @@ -157,3 +206,16 @@ export enum MetricsMultiClassification { Recall = 'recall_score', F1 = 'f1_score', } + +export enum BatchSize { + O1 = '2', + O2 = '4', + O3 = '8', + O4 = '16', + O5 = '32', + O6 = '64', + O7 = '128', + O8 = '256', + O9 = '512', + O10 = '1024' +}
\ No newline at end of file |