LogisticRegression
Extends:
lib/deep_learning.js~BaseNeuralNetwork → LogisticRegression
Implements:
Logistic Regression Classification with Tensorflow
Constructor Summary
Public Constructor | ||
public |
constructor(options: {layers: Array<Object>, compile: Object, fit: Object}, properties: *) |
Method Summary
Public Methods | ||
public |
generateLayers(x_matrix: Array<Array<number>>, y_matrix: Array<Array<number>>, layers: Array<Object>, x_test: Array<Array<number>>, y_test: Array<Array<number>>) Adds dense layers to tensorflow classification model |
Public Constructors
public constructor(options: {layers: Array<Object>, compile: Object, fit: Object}, properties: *) source
Params:
Name | Type | Attribute | Description |
options | {layers: Array<Object>, compile: Object, fit: Object} | neural network configuration and tensorflow model hyperparameters |
|
properties | * | extra instance properties |
Public Methods
public generateLayers(x_matrix: Array<Array<number>>, y_matrix: Array<Array<number>>, layers: Array<Object>, x_test: Array<Array<number>>, y_test: Array<Array<number>>) source
Adds dense layers to tensorflow classification model
Params:
Name | Type | Attribute | Description |
x_matrix | Array<Array<number>> | independent variables |
|
y_matrix | Array<Array<number>> | dependent variables |
|
layers | Array<Object> | model dense layer parameters |
|
x_test | Array<Array<number>> | validation data independent variables |
|
y_test | Array<Array<number>> | validation data dependent variables |