Ml4qc

Latest version: v0.1.10

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0.1.10

Fixed to support cases where OLS controls aren't specified. Updated copyright to 2023.

0.1.9

Added support for OLS controls during pre-processing, to control out effects of nonrandom assignment.

0.1.8

Fixed package requirements.

0.1.7

Added cluster and enumerator analysis.

0.1.6

Added support for probability calibration and threshold tuning, shifted to new preferred approach where custom thresholds and calibrated probability distributions are used rather than reweighting for imbalanced classes. Other changes: removed reweight_classes constructor parameter (but just always calculate weights in case people want to use them); used random_state for tensorflow seed; tweaked verbose outputs; stopped collecting and reporting average_precision; reverted to current (vs. legacy) Adam optimizer for tensorflow, as they seem to have resolved the problem with cross-validation (and a problem with the legacy Adam optimizer emerged).

0.1.5

Increased coverage for random_state support, and added n_jobs support at the ml4qc class level, for control over cross-validation parallelization.

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