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cppyml 0.8.0 documentation
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A
absolute_tolerance (cppyml.logistic_regression.LogisticRegression attribute)
adjusted_r2 (cppyml.linear_regression.Result attribute)
assign_label() (cppyml.clustering.KMeans method)
assign_responsibilities() (cppyml.clustering.EM method)
B
beta (cppyml.linear_regression.LassoRegressionResult attribute)
(cppyml.linear_regression.MultivariateOLSResult attribute)
(cppyml.linear_regression.RecursiveMultivariateOLS attribute)
(cppyml.linear_regression.RidgeRegressionResult attribute)
C
centroids (cppyml.clustering.KMeans attribute)
CentroidsInitialiser (class in cppyml.clustering)
classification_tree() (in module cppyml.decision_trees)
classification_tree_accuracy() (in module cppyml.decision_trees)
ClassificationTree (class in cppyml.decision_trees)
ClosestCentroid (class in cppyml.clustering)
ConjugateGradientLogisticRegression (class in cppyml.logistic_regression)
converged (cppyml.logistic_regression.Result attribute)
cost_complexity() (cppyml.decision_trees.ClassificationTree method)
(cppyml.decision_trees.RegressionTree method)
cov (cppyml.linear_regression.MultivariateOLSResult attribute)
(cppyml.linear_regression.RidgeRegressionResult attribute)
cov_slope_intercept (cppyml.linear_regression.UnivariateOLSResult attribute)
covariance() (cppyml.clustering.EM method)
cppyml (module)
cppyml.clustering (module)
cppyml.decision_trees (module)
cppyml.linear_regression (module)
cppyml.logistic_regression (module)
D
d (cppyml.linear_regression.RecursiveMultivariateOLS attribute)
dof (cppyml.linear_regression.Result attribute)
E
effective_dof (cppyml.linear_regression.LassoRegressionResult attribute)
(cppyml.linear_regression.RidgeRegressionResult attribute)
EM (class in cppyml.clustering)
F
fit() (cppyml.clustering.EM method)
(cppyml.clustering.KMeans method)
(cppyml.logistic_regression.LogisticRegression method)
Forgy (class in cppyml.clustering)
I
inertia (cppyml.clustering.KMeans attribute)
intercept (cppyml.linear_regression.UnivariateOLSResult attribute)
K
KMeans (class in cppyml.clustering)
KPP (class in cppyml.clustering)
L
labels (cppyml.clustering.KMeans attribute)
lam (cppyml.logistic_regression.LogisticRegression attribute)
lasso() (in module cppyml.linear_regression)
LassoRegressionResult (class in cppyml.linear_regression)
log_likelihood (cppyml.clustering.EM attribute)
LogisticRegression (class in cppyml.logistic_regression)
M
maximum_steps (cppyml.logistic_regression.LogisticRegression attribute)
means (cppyml.clustering.EM attribute)
mixing_probabilities (cppyml.clustering.EM attribute)
multivariate() (in module cppyml.linear_regression)
MultivariateOLSResult (class in cppyml.linear_regression)
N
n (cppyml.linear_regression.RecursiveMultivariateOLS attribute)
(cppyml.linear_regression.Result attribute)
number_clusters (cppyml.clustering.KMeans attribute)
number_components (cppyml.clustering.EM attribute)
number_leaf_nodes (cppyml.decision_trees.ClassificationTree attribute)
(cppyml.decision_trees.RegressionTree attribute)
number_lowest_split_nodes (cppyml.decision_trees.ClassificationTree attribute)
(cppyml.decision_trees.RegressionTree attribute)
number_nodes (cppyml.decision_trees.ClassificationTree attribute)
(cppyml.decision_trees.RegressionTree attribute)
O
original_error (cppyml.decision_trees.ClassificationTree attribute)
(cppyml.decision_trees.RegressionTree attribute)
P
predict() (cppyml.logistic_regression.Result method)
press() (in module cppyml.linear_regression)
press_univariate() (in module cppyml.linear_regression)
R
r2 (cppyml.linear_regression.Result attribute)
RandomPartition (class in cppyml.clustering)
RecursiveMultivariateOLS (class in cppyml.linear_regression)
regression_tree() (in module cppyml.decision_trees)
regression_tree_mean_squared_error() (in module cppyml.decision_trees)
RegressionTree (class in cppyml.decision_trees)
relative_tolerance (cppyml.logistic_regression.LogisticRegression attribute)
responsibilities (cppyml.clustering.EM attribute)
ResponsibilitiesInitialiser (class in cppyml.clustering)
Result (class in cppyml.linear_regression)
(class in cppyml.logistic_regression)
ridge() (in module cppyml.linear_regression)
RidgeRegressionResult (class in cppyml.linear_regression)
rss (cppyml.linear_regression.Result attribute)
S
set_absolute_tolerance() (cppyml.clustering.EM method)
(cppyml.clustering.KMeans method)
(cppyml.logistic_regression.LogisticRegression method)
set_centroids_initialiser() (cppyml.clustering.KMeans method)
set_lam() (cppyml.logistic_regression.LogisticRegression method)
set_maximise_first() (cppyml.clustering.EM method)
set_maximum_steps() (cppyml.clustering.EM method)
(cppyml.clustering.KMeans method)
(cppyml.logistic_regression.LogisticRegression method)
set_means_initialiser() (cppyml.clustering.EM method)
set_number_initialisations() (cppyml.clustering.KMeans method)
set_relative_tolerance() (cppyml.clustering.EM method)
(cppyml.logistic_regression.LogisticRegression method)
set_responsibilities_initialiser() (cppyml.clustering.EM method)
set_seed() (cppyml.clustering.EM method)
(cppyml.clustering.KMeans method)
set_verbose() (cppyml.clustering.EM method)
(cppyml.clustering.KMeans method)
slope (cppyml.linear_regression.UnivariateOLSResult attribute)
steps_taken (cppyml.logistic_regression.Result attribute)
T
total_leaf_error (cppyml.decision_trees.ClassificationTree attribute)
(cppyml.decision_trees.RegressionTree attribute)
tss (cppyml.linear_regression.Result attribute)
U
univariate() (in module cppyml.linear_regression)
univariate_regular() (in module cppyml.linear_regression)
univariate_without_intercept() (in module cppyml.linear_regression)
UnivariateOLSResult (class in cppyml.linear_regression)
update() (cppyml.linear_regression.RecursiveMultivariateOLS method)
V
var_intercept (cppyml.linear_regression.UnivariateOLSResult attribute)
var_slope (cppyml.linear_regression.UnivariateOLSResult attribute)
var_y (cppyml.linear_regression.Result attribute)
W
w (cppyml.logistic_regression.Result attribute)
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cppyml 0.8.0 documentation
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