Package statkit
Statistics for machine learning.
Brings traditional (frequentistic) statistical concepts to your sci-kit learn models.
Examples
- Hypothesis testing of model scores with p-values (see, e.g.,
unpaired_permutation_test()
), - Estimate 95 % confidence intervals around test scores (see, e.g.,
bootstrap_score()
). - Decision curve analysis to compare models in terms of consequences of actions
(see, e.g.,
NetBenefitDisplay
). - Downsample a dataset while matching/stratifying on continuous/discrete variables
to balance the groups (see, e.g.,
balanced_downsample()
). - Univariate feature selection with multiple hypothesis testing correction (see,
e.g.,
StatisticalTestFilter
),
Expand source code
r"""Statistics for machine learning.
Brings traditional (frequentistic) statistical concepts to your sci-kit learn models.
Examples:
- Hypothesis testing of model scores with \(p\)-values (see, e.g.,
`statkit.non_parametric.unpaired_permutation_test`),
- Estimate 95 % confidence intervals around test scores (see, e.g.,
`statkit.non_parametric.bootstrap_score`).
- Decision curve analysis to compare models in terms of consequences of actions
(see, e.g., `statkit.decision.NetBenefitDisplay`).
- Downsample a dataset while matching/stratifying on continuous/discrete variables
to balance the groups (see, e.g., `statkit.dataset.balanced_downsample`).
- Univariate feature selection with multiple hypothesis testing correction (see,
e.g.,
`statkit.feature_selection.StatisticalTestFilter`),
"""
__version__ = "0.2.7"
Sub-modules
statkit.dataset
-
Various methods for partitioning the dataset, such as downsampling and splitting.
statkit.decision
-
Evaluate models using decision curve analysis.
statkit.feature_selection
-
Select features using statistical hypothesis testing.
statkit.metrics
-
Classification metrics not part of sci-kit learn.
statkit.model_selection
statkit.non_parametric
-
Confidence intervals and p-values of a model's (test) score …
statkit.power
-
Estimate population size needed to reject null hypothesis for a given metric.
statkit.types
statkit.views