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export default class Model {
_id: string = '';
constructor(
public name: string = 'Novi model',
public description: string = '',
public dateCreated: Date = new Date(),
public lastUpdated: Date = new Date(),
public datasetId: string = '',
// Test set settings
public inputColumns: string[] = [],
public columnToPredict: string = '',
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
// Neural net training settings
public type: ProblemType = ProblemType.Regression,
public encoding: Encoding = Encoding.Label,
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 = 5,
public hiddenLayerActivationFunctions: string[] = ['sigmoid'],
//public inputLayerActivationFunction: ActivationFunction = ActivationFunction.Sigmoid,
public outputLayerActivationFunction: ActivationFunction = ActivationFunction.Sigmoid,
public username: string = '',
public nullValues: NullValueOptions = NullValueOptions.DeleteRows,
public nullValuesReplacers: NullValReplacer[] = [],
public metrics: Metric[] = [], // TODO add to add-model form
public epochs: number = 5 // TODO add to add-model form
) { }
}
export enum ProblemType {
Regression = 'regresioni',
BinaryClassification = 'binarni-klasifikacioni',
MultiClassification = 'multi-klasifikacioni'
}
// replaceMissing srednja vrednost mean, median, najcesca vrednost (mode)
// removeOutliers
export enum Encoding {
Label = 'label',
OneHot = 'one hot',
BackwardDifference = 'backward difference',
BaseN = 'baseN',
Binary = 'binary',
CatBoost = 'cat boost',
Count = 'count',
GLMM = 'glmm',
Hashing = 'hashing',
Helmert = 'helmert',
JamesStein = 'james stein',
LeaveOneOut = 'leave one out',
MEstimate = 'MEstimate',
Ordinal = 'ordinal',
Sum = 'sum',
Polynomial = 'polynomial',
Target = 'target',
WOE = 'woe',
Quantile = 'quantile'
}
export enum ActivationFunction {
// linear
Binary_Step = 'binaryStep',
Linear = 'linear',
// non-linear
Relu = 'relu',
Leaky_Relu = 'leakyRelu',
Parameterised_Relu = 'parameterisedRelu',
Exponential_Linear_Unit = 'exponentialLinearUnit',
Swish = 'swish',
Sigmoid = 'sigmoid',
Tanh = 'tanh',
Softmax = 'softmax'
}
export enum LossFunction {
// binary classification loss functions
BinaryCrossEntropy = 'binary_crossentropy',
HingeLoss = 'hinge_loss',
// multi-class classiication loss functions
CategoricalCrossEntropy = 'categorical_crossentropy',
KLDivergence = 'kullback_leibler_divergence',
// regression loss functions
MeanSquaredError = 'mean_squared_error',
MeanAbsoluteError = 'mean_absolute_error',
HuberLoss = 'Huber',
}
export enum Optimizer {
Adam = 'Adam',
Adadelta = 'Adadelta',
Adagrad = 'Adagrad',
Ftrl = 'Ftrl',
Nadam = 'Nadam',
SGD = 'SGD',
SGDMomentum = 'SGDMomentum',
RMSprop = 'RMSprop'
}
export enum NullValueOptions {
DeleteRows = 'delete_rows',
DeleteColumns = 'delete_columns',
Replace = 'replace'
}
export enum ReplaceWith {
None = 'Popuni...',
Mean = 'Srednja vrednost',
Median = 'Medijana'
}
export class NullValReplacer {
"column": string;
"option": NullValueOptions;
"value" : string;
}
export enum Metric {
MSE = 'mse',
MAE = 'mae',
RMSE = 'rmse'
//...
}
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