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Deep Learning Classification, LSTM Time Series, Regression and Multi-Layered Perceptrons with Tensorflow

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import { TensorScriptModelInterface, TensorScriptOptions, TensorScriptProperties, Matrix, Vector, TensorScriptLayers, TensorScriptSavedLayers, PredictionOptions } from './model_interface'; /** * Deep Learning with Tensorflow * @class BaseNeuralNetwork * @implements {TensorScriptModelInterface} */ export declare class BaseNeuralNetwork extends TensorScriptModelInterface { /** * @param {{layers:Array<Object>,compile:Object,fit:Object}} options - neural network configuration and tensorflow model hyperparameters * @param {{model:Object,tf:Object,}} properties - extra instance properties */ constructor(options?: TensorScriptOptions, properties?: TensorScriptProperties); /** * Adds dense layers to tensorflow model * @abstract * @param {Array<Array<number>>} x_matrix - independent variables * @param {Array<Array<number>>} y_matrix - dependent variables * @param {Array<Object>} layers - model dense layer parameters */ generateLayers(x_matrix: Matrix, y_matrix: Matrix, layers?: TensorScriptLayers | TensorScriptSavedLayers, x_test?: Matrix, y_test?: Matrix): void; /** * Asynchronously trains tensorflow model * @override * @param {Array<Array<number>>} x_matrix - independent variables * @param {Array<Array<number>>} y_matrix - dependent variables * @param {Array<Object>} layers - array of model dense layer parameters * @param {Array<Array<number>>} x_text - validation data independent variables * @param {Array<Array<number>>} y_text - validation data dependent variables * @return {Object} returns trained tensorflow model */ train(x_matrix: Matrix, y_matrix: Matrix, layers?: TensorScriptLayers, x_test?: Matrix, y_test?: Matrix): Promise<any>; /** * Predicts new dependent variables * @override * @param {Array<Array<number>>|Array<number>} matrix - new test independent variables * @param {Object} options - model prediction options * @return {{data: Promise}} returns tensorflow prediction */ calculate(input_matrix: Matrix | Vector, options?: PredictionOptions): any; }