Index

_

_data (attribut trainedml.viz.vizs.Vizs)

_figure (attribut trainedml.viz.vizs.Vizs) _save_path (attribut trainedml.viz.vizs.Vizs)

A

analyzer (attribut trainedml.visualization.Visualizer)

auto_evaluate() (méthode statique trainedml.evaluation.Evaluator)

B

Benchmark (classe dans trainedml.benchmark) bins (attribut trainedml.viz.histogram.HistogramViz) bivariate() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer)

BivariateViz (classe dans trainedml.viz.bivariate) boxplot() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) BoxplotViz (classe dans trainedml.viz.boxplot) build_preprocessor() (dans le module trainedml.preprocessing)

C

columns (attribut trainedml.viz.histogram.HistogramViz) compare() (dans le module trainedml) correlation() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer)

correlation_matrix() (dans le module trainedml.viz.correlation) CorrelationViz (classe dans trainedml.viz.correlation)

D

data (attribut trainedml.analyzer.DataAnalyzer) (attribut trainedml.visualization.Visualizer) (attribut trainedml.viz.bivariate.BivariateViz) (attribut trainedml.viz.heatmap.HeatmapViz) (attribut trainedml.viz.histogram.HistogramViz) DataAnalyzer (classe dans trainedml.analyzer)

DataLoader (classe dans trainedml.data.loader) detect_model_task() (dans le module trainedml.tasks) detect_task() (dans le module trainedml.tasks) distribution() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) distribution_summary() (dans le module trainedml.viz.distribution) DistributionViz (classe dans trainedml.viz.distribution)

E

evaluate() (méthode trainedml.Trainer) evaluate_all() (méthode statique trainedml.evaluation.Evaluator)

evaluate_for() (méthode statique trainedml.evaluation.Evaluator) evaluate_regression() (méthode statique trainedml.evaluation.Evaluator) Evaluator (classe dans trainedml.evaluation)

F

features (attribut trainedml.viz.heatmap.HeatmapViz) figure (attribut trainedml.viz.bivariate.BivariateViz) (attribut trainedml.viz.heatmap.HeatmapViz) (attribut trainedml.viz.histogram.HistogramViz) (propriété trainedml.viz.vizs.Vizs)

fit() (méthode trainedml.preprocessing.PreprocessedModel) (méthode trainedml.Trainer)

G

generate_report() (dans le module trainedml.report)

get_features() (méthode trainedml.visualization.Visualizer)

H

heatmap() (méthode trainedml.visualization.Visualizer) HeatmapViz (classe dans trainedml.viz.heatmap)

histogram() (méthode trainedml.visualization.Visualizer) HistogramViz (classe dans trainedml.viz.histogram)

I

is_classification_target() (dans le module trainedml.tasks)

is_fitted (attribut trainedml.Trainer)

L

legend (attribut trainedml.viz.histogram.HistogramViz) line() (méthode trainedml.visualization.Visualizer) LineViz (classe dans trainedml.viz.line)

load() (méthode de la classe trainedml.Trainer) load_csv_from_url() (méthode trainedml.data.loader.DataLoader) load_data() (méthode trainedml.Trainer) load_dataset() (méthode trainedml.data.loader.DataLoader)

M

mask (attribut trainedml.viz.heatmap.HeatmapViz) MAX_UNIQUE_FOR_CLASSIFICATION (dans le module trainedml.tasks) method (attribut trainedml.viz.heatmap.HeatmapViz) missing() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) missing_summary() (dans le module trainedml.viz.missing) MissingValuesViz (classe dans trainedml.viz.missing) model (attribut trainedml.preprocessing.PreprocessedModel) (attribut trainedml.Trainer) models (attribut trainedml.benchmark.Benchmark) module trainedml trainedml.analyzer trainedml.benchmark trainedml.data.loader trainedml.evaluation trainedml.preprocessing trainedml.report trainedml.tasks trainedml.visualization trainedml.viz.bivariate trainedml.viz.boxplot trainedml.viz.correlation trainedml.viz.distribution trainedml.viz.heatmap trainedml.viz.histogram trainedml.viz.line trainedml.viz.missing trainedml.viz.multicollinearity trainedml.viz.normality trainedml.viz.outliers trainedml.viz.profiling trainedml.viz.target trainedml.viz.vizs

multicollinearity() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) MulticollinearityViz (classe dans trainedml.viz.multicollinearity)

N

normality() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer)

normality_tests() (dans le module trainedml.viz.normality) NormalityViz (classe dans trainedml.viz.normality)

O

outlier_summary() (dans le module trainedml.viz.outliers) outliers() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer)

OutliersViz (classe dans trainedml.viz.outliers)

P

predict() (méthode trainedml.preprocessing.PreprocessedModel) (méthode trainedml.Trainer) PreprocessedModel (classe dans trainedml.preprocessing) preprocessor (attribut trainedml.preprocessing.PreprocessedModel) (attribut trainedml.Trainer)

print_summary() (méthode trainedml.benchmark.Benchmark), [1] profiling() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) profiling_report() (dans le module trainedml.viz.profiling) ProfilingViz (classe dans trainedml.viz.profiling)

R

report() (méthode trainedml.visualization.Visualizer) results (attribut trainedml.benchmark.Benchmark)

run() (méthode trainedml.benchmark.Benchmark), [1] run_cv() (méthode trainedml.benchmark.Benchmark)

S

save() (méthode trainedml.Trainer) (méthode trainedml.viz.vizs.Vizs)

save_path (propriété trainedml.viz.vizs.Vizs) split() (méthode trainedml.data.loader.DataLoader) summary() (méthode trainedml.benchmark.Benchmark), [1]

T

target() (méthode trainedml.analyzer.DataAnalyzer) (méthode trainedml.visualization.Visualizer) TargetViz (classe dans trainedml.viz.target) task (attribut trainedml.preprocessing.PreprocessedModel) (attribut trainedml.Trainer) (propriété trainedml.preprocessing.PreprocessedModel) (propriété trainedml.Trainer) to_dataframe() (méthode trainedml.benchmark.Benchmark) trainedml module trainedml.analyzer module trainedml.benchmark module trainedml.data.loader module trainedml.evaluation module trainedml.preprocessing module trainedml.report module trainedml.tasks module trainedml.visualization module trainedml.viz.bivariate module

trainedml.viz.boxplot module trainedml.viz.correlation module trainedml.viz.distribution module trainedml.viz.heatmap module trainedml.viz.histogram module trainedml.viz.line module trainedml.viz.missing module trainedml.viz.multicollinearity module trainedml.viz.normality module trainedml.viz.outliers module trainedml.viz.profiling module trainedml.viz.target module trainedml.viz.vizs module Trainer (classe dans trainedml)

V

vif_summary() (dans le module trainedml.viz.multicollinearity) Visualizer (classe dans trainedml.visualization) Vizs (classe dans trainedml.viz.vizs) vizs() (méthode trainedml.viz.bivariate.BivariateViz) (méthode trainedml.viz.boxplot.BoxplotViz) (méthode trainedml.viz.correlation.CorrelationViz) (méthode trainedml.viz.distribution.DistributionViz) (méthode trainedml.viz.heatmap.HeatmapViz) (méthode trainedml.viz.histogram.HistogramViz) (méthode trainedml.viz.line.LineViz) (méthode trainedml.viz.missing.MissingValuesViz) (méthode trainedml.viz.multicollinearity.MulticollinearityViz) (méthode trainedml.viz.normality.NormalityViz) (méthode trainedml.viz.outliers.OutliersViz) (méthode trainedml.viz.profiling.ProfilingViz) (méthode trainedml.viz.target.TargetViz) (méthode trainedml.viz.vizs.Vizs)

X

x (attribut trainedml.viz.bivariate.BivariateViz)

Y

y (attribut trainedml.viz.bivariate.BivariateViz)