neural network configuration and tensorflow model hyperparameters
Optional
properties: TensorScriptPropertiesextra instance properties
Rest
...args: any[]Optional
getOptional
layersOptional
lossRest
...args: any[]Optional
xOptional
yAdds dense layers to tensorflow classification model
independent variables
dependent variables
model dense layer parameters
validation data independent variables
validation data dependent variables
Loads a saved tensoflow / keras model, this is an alias for
tensorflow model
https://www.tensorflow.org/js/guide/save_load#loading_a_tfmodel
tensorflow load model options
Returns prediction values from tensorflow model
predicted model values
Optional
input_matrix: Matrix | Vector | PredictionOptions | InputTextArraynew test independent variables
Optional
options: PredictionOptionssaves a tensorflow model, this is an alias for
tensorflow model
https://www.tensorflow.org/js/guide/save_load#save_a_tfmodel
tensorflow save model options
Asynchronously trains tensorflow model
returns trained tensorflow model
independent variables
dependent variables
Optional
layers: TensorScriptLayersarray of model dense layer parameters
Optional
x_test: MatrixOptional
y_test: MatrixStatic
getStatic
reshapeReshapes an array
const array = [ 0, 1, 1, 0, ];
const shape = [2,2];
TensorScriptModelInterface.reshape(array,shape) // =>
[
[ 0, 1, ],
[ 1, 0, ],
];
returns a matrix with the defined shape
input array
shape array
Logistic Regression Classification with Tensorflow
Implements