Index

_

_best_split() (scripts.models.decision_tree.DecisionTree method) _check_criterion() (scripts.models.decision_tree.DecisionTree method) _evaluate_leaf() (scripts.models.decision_tree.DecisionTree method) _get_child_info() (scripts.models.decision_tree.DecisionTree method) _is_pure() (scripts.models.decision_tree.DecisionTree method)

_parameters() (scripts.models.neural_net.NeuralNetworkClassifier method) _run_init_setup() (scripts.models.decision_tree.DecisionTree method) _run_training_setup() (scripts.models.decision_tree.DecisionTree method) _split() (scripts.models.decision_tree.DecisionTree method) _total_parameters() (scripts.models.neural_net.NeuralNetworkClassifier method)

A

accuracy_history (scripts.models.neural_net.NeuralNetworkClassifier attribute) accuracy_score() (in module scripts.metrics._classification)

add() (scripts.models.neural_net.NeuralNetworkClassifier method) ae() (in module scripts.metrics._loss)

B

backward() (scripts.models.neural_net.Var method)

BaseClassifier (class in scripts.base) BaseModel (class in scripts.base)

C

check_consistent_length() (in module scripts.utils) classes() (scripts.base.BaseClassifier method) classification_error() (in module scripts.metrics._classification)

classification_report() (in module scripts.metrics._classification) confusion_matrix() (in module scripts.metrics._classification) cross_entropy() (in module scripts.metrics._loss)

D

decision() (scripts.models.decision_tree.Node method) DecisionTree (class in scripts.models.decision_tree)

DecisionTreeClassifier (class in scripts.models.decision_tree) DenseLayer (class in scripts.models.neural_net) dim() (scripts.models.neural_net.DenseLayer method)

E

entropy() (in module scripts.metrics._split)

exp() (scripts.models.neural_net.Var method)

F

f1_score() (in module scripts.metrics._classification) fit() (scripts.models.decision_tree.DecisionTree method) (scripts.models.neural_net.NeuralNetworkClassifier method)

fitted (scripts.models.neural_net.NeuralNetworkClassifier attribute) forward() (scripts.models.neural_net.DenseLayer method) (scripts.models.neural_net.NeuralNetworkClassifier method)

G

generate_summary() (in module scripts.utils) get_data() (in module scripts.utils)

gini() (in module scripts.metrics._split) grad (scripts.models.neural_net.Var attribute)

I

is_fitted() (scripts.base.BaseModel method)

is_leaf() (scripts.models.decision_tree.Node method)

K

k (scripts.models.neural_net.NeuralNetworkClassifier attribute)

L

left (scripts.models.decision_tree.Node attribute) log() (scripts.models.neural_net.Var method)

loss (scripts.models.decision_tree.Node attribute) loss_history (scripts.models.neural_net.NeuralNetworkClassifier attribute)

M

ModelNotFittedError module scripts.base scripts.metrics._classification scripts.metrics._loss scripts.metrics._split scripts.models.decision_tree scripts.models.neural_net scripts.plotting scripts.utils

N

n (scripts.models.neural_net.NeuralNetworkClassifier attribute) NeuralNetworkClassifier (class in scripts.models.neural_net) neurons() (scripts.models.neural_net.DenseLayer method) Node (class in scripts.models.decision_tree) num_leaf_nodes (scripts.models.decision_tree.DecisionTree attribute)

num_nodes (scripts.models.decision_tree.DecisionTree attribute) num_params() (scripts.models.neural_net.DenseLayer method) number_of_classes() (scripts.base.BaseClassifier method) number_of_features() (scripts.base.BaseModel method) number_of_training_samples() (scripts.base.BaseModel method)

P

p (scripts.models.decision_tree.Node attribute) (scripts.models.neural_net.NeuralNetworkClassifier attribute) parameters (scripts.models.neural_net.NeuralNetworkClassifier attribute) parameters() (scripts.models.neural_net.DenseLayer method) plot_1d_decision_regions() (in module scripts.plotting) plot_2d_decision_regions() (in module scripts.plotting)

precision_score() (in module scripts.metrics._classification) predict (scripts.models.decision_tree.Node attribute) predict() (scripts.models.decision_tree.DecisionTree method) (scripts.models.neural_net.NeuralNetworkClassifier method) predict_proba (scripts.models.decision_tree.Node attribute) predict_proba() (scripts.models.decision_tree.DecisionTree method) (scripts.models.neural_net.NeuralNetworkClassifier method)

R

recall_score() (in module scripts.metrics._classification) relu() (scripts.models.neural_net.Var method)

right (scripts.models.decision_tree.Node attribute) root (scripts.models.decision_tree.DecisionTree attribute)

S

score() (scripts.base.BaseClassifier method) scripts.base module scripts.metrics._classification module scripts.metrics._loss module scripts.metrics._split module scripts.models.decision_tree module

scripts.models.neural_net module scripts.plotting module scripts.utils module se() (in module scripts.metrics._loss) split (scripts.models.decision_tree.Node attribute) summary() (scripts.models.neural_net.NeuralNetworkClassifier method)

T

tanh() (scripts.models.neural_net.Var method)

V

val (scripts.models.decision_tree.Node attribute) validate_feature_matrix() (in module scripts.utils)

validate_target_vector() (in module scripts.utils) Var (class in scripts.models.neural_net)

X

X (scripts.models.neural_net.NeuralNetworkClassifier attribute)

Y

y (scripts.models.neural_net.NeuralNetworkClassifier attribute)

y_hot (scripts.models.neural_net.NeuralNetworkClassifier attribute)

Z

zero_one_loss() (in module scripts.metrics._loss)