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Functions368 in github.com/rushter/MLAlgorithms

Functionrelu
(z)
mla/neuralnet/activations.py:38
Functionroot_mean_squared_error
(actual, predicted)
mla/metrics/metrics.py:54
Functionroot_mean_squared_log_error
(actual, predicted)
mla/metrics/metrics.py:58
Methodsetup
Creates additional variables. Note: Must be called before optimization process.
mla/neuralnet/optimizers.py:65
Methodsetup
(self, network)
mla/neuralnet/optimizers.py:115
Methodsetup
(self, network)
mla/neuralnet/optimizers.py:148
Methodsetup
(self, network)
mla/neuralnet/optimizers.py:174
Methodsetup
(self, network)
mla/neuralnet/optimizers.py:211
Methodsetup
(self, network)
mla/neuralnet/optimizers.py:245
Methodsetup
(self, x_shape)
mla/neuralnet/layers/basic.py:68
Methodsetup
(self, X_shape)
mla/neuralnet/layers/basic.py:159
Methodsetup
(self, X_shape)
mla/neuralnet/layers/convnet.py:41
Methodsetup
(self, x_shape)
mla/neuralnet/layers/normalization.py:24
Methodsetup
Parameters ---------- x_shape : np.array(batch size, time steps, input shape)
mla/neuralnet/layers/recurrent/rnn.py:35
Methodsetup
Naming convention: i : input gate f : forget gate c : cell o : output gate Parameters ------
mla/neuralnet/layers/recurrent/lstm.py:47
Methodshape
(self, x_shape)
mla/neuralnet/layers/basic.py:88
Methodshape
(self, x_shape)
mla/neuralnet/layers/basic.py:106
Methodshape
(self, x_shape)
mla/neuralnet/layers/basic.py:130
Methodshape
(self, x_shape)
mla/neuralnet/layers/basic.py:146
Methodshape
(self, x_shape)
mla/neuralnet/layers/basic.py:182
Methodshape
(self, x_shape)
mla/neuralnet/layers/convnet.py:122
Methodshape
(self, x_shape)
mla/neuralnet/layers/convnet.py:139
Methodshape
(self, x_shape)
mla/neuralnet/layers/normalization.py:157
Methodshape
(self, x_shape)
mla/neuralnet/layers/recurrent/rnn.py:106
Methodshape
(self, x_shape)
mla/neuralnet/layers/recurrent/lstm.py:191
Functionsoftsign
(z)
mla/neuralnet/activations.py:30
Functiontanh
(z)
mla/neuralnet/activations.py:34
Functiontest_PCA
(dataset)
mla/tests/test_reduction.py:30
Functiontest_absolute_error
()
mla/metrics/tests/test_metrics.py:35
Functiontest_adadelta
()
mla/neuralnet/tests/test_optimizers.py:49
Functiontest_adagrad
()
mla/neuralnet/tests/test_optimizers.py:65
Functiontest_adam
()
mla/neuralnet/tests/test_optimizers.py:53
Functiontest_adamax
()
mla/neuralnet/tests/test_optimizers.py:57
Functiontest_classification_error
()
mla/metrics/tests/test_metrics.py:28
Functiontest_data_validation
()
mla/metrics/tests/test_metrics.py:11
Functiontest_gbm
()
mla/tests/test_classification_accuracy.py:93
Functiontest_knn
()
mla/tests/test_regression_accuracy.py:57
Functiontest_knn
()
mla/tests/test_classification_accuracy.py:109
Functiontest_linear
()
mla/tests/test_regression_accuracy.py:30
Functiontest_linear_model
()
mla/tests/test_classification_accuracy.py:43
Functiontest_mean_absolute_error
()
mla/metrics/tests/test_metrics.py:41
Functiontest_mean_squared_error
()
mla/metrics/tests/test_metrics.py:72
Functiontest_mean_squared_log_error
()
mla/metrics/tests/test_metrics.py:60
Functiontest_mlp
()
mla/tests/test_regression_accuracy.py:37
Functiontest_mlp
()
mla/tests/test_classification_accuracy.py:68
Functiontest_multiclass_logloss
()
mla/metrics/tests/test_metrics.py:84
Functiontest_naive_bayes
()
mla/tests/test_classification_accuracy.py:102
Functiontest_random_forest
()
mla/tests/test_classification_accuracy.py:50
Functiontest_rmsprop
()
mla/neuralnet/tests/test_optimizers.py:61
Functiontest_root_mean_squared_error
()
mla/metrics/tests/test_metrics.py:78
Functiontest_root_mean_squared_log_error
()
mla/metrics/tests/test_metrics.py:66
Functiontest_sgd
()
mla/neuralnet/tests/test_optimizers.py:69
Functiontest_softplus
()
mla/neuralnet/tests/test_activations.py:8
Functiontest_squared_error
()
mla/metrics/tests/test_metrics.py:47
Functiontest_squared_log_error
()
mla/metrics/tests/test_metrics.py:53
Functiontest_svm_classification
()
mla/tests/test_classification_accuracy.py:57
Methodtrain_batch
(self, network, X, y)
mla/neuralnet/optimizers.py:60
Methodtransform
(self, output)
mla/ensemble/gbm.py:71
Functionunhot
Convert one-hot representation into one column.
mla/metrics/metrics.py:7
Methodupdate
(self, X, y)
mla/neuralnet/nnet.py:94
Methodupdate
(self, network)
mla/neuralnet/optimizers.py:107
Methodupdate
(self, network)
mla/neuralnet/optimizers.py:129
Methodupdate
(self, network)
mla/neuralnet/optimizers.py:164
Methodupdate
(self, network)
mla/neuralnet/optimizers.py:191
Methodupdate
(self, network)
mla/neuralnet/optimizers.py:229
Functionwrapper
(a, b)
mla/metrics/base.py:21
Functionwrapper
(actual, predicted)
mla/metrics/metrics.py:10
Functionzero
(shape, **kwargs)
mla/neuralnet/initializations.py:18
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