feature_engine

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feat: Random Noise Selection method

10

**Is your feature request related to a problem? Please describe.** Filtering Noisy features from a set of features can be easily accomplished by adding a one or more random variables...

TremaMiguel

feat: Kmeans Encode Categorical Feature

11

**Is your feature request related to a problem? Please describe.** From [Kaggle](https://www.kaggle.com/ryanholbrook/clustering-with-k-means) > The motivating idea for adding cluster labels is that the clusters will break up complicated relationships across...

TremaMiguel

DecisionTreeDiscretiser to output integers in addition to the predictions

5

At the moment, the DecisionTreeDiscretiser returns the values of the tree predictions as the replacement of the original variables. I would like to add the option to return integers from...

solegalli

Add new class to substract datetime variables

16

This code needs unit tests, but I wanted to get feedback on this newer implementation of the class. closes stale PR #359

kylegilde

Ignore NaNs before using `OrdinalEncoder`

1

*Is your feature request related to a problem?* `OrdinalEncoder` should accept nulls. Sometimes you don't want to impute directly but using Imputing Options of XGBoost, LightGBM or CatBoost. Because of...

datacubeR

Smoothing on Mean Encoder

14

**Is your feature request related to a problem? Please describe.** Hi Sole, currently Im doing the mini course of [feature engineering](https://www.kaggle.com/ryanholbrook/target-encoding) on kaggle. The last seccion is about Mean Encoding...

hectorpatino

Polynomial Feaatures + SklearnWrapper weird behavior

3

**Describe the bug** A clear and concise description of what the bug is. When using PolynomialFeaturs + SklearnWrappers the base features are duplicated, when trying to dedup using DropDuplicateFeatures the...

datacubeR

TargetMeanDiscretiser: sorts variables in bins and replaces bins by target mean value

19

Closes #394. The transformer accepts a dictionary that defines how numeric variables will be discretized/organized into bins. The transformer calculates and returns the average for the respective bins.

Morgan-Sell

multivariate imputation

4

In multivariate imputation, we estimate the values of missing data using regression or classification models based of the other variables in the data. The iterativeimputer will allows us only to...

solegalli

Create check_y_is_binary() check. Use in transformers in which the dependent variable must be binary.

2

Closes #413 Notes from #413: Many transformers in feature engine require that y is binary. At the moment we do this check within each transformer. We should create a function...

Morgan-Sell