Forward Selection using KNN Algorithm in Pandas

Question

Could anyone help me on how to do a forward selection from a dataset using KNN Algorithm in Pandas ?

https://scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html

I followed this website but it doesn't look like a forward selection and it is not using KNN Algorithm.

• The input is the dataset and Target Variable.
• The output should be a list of forward selected features.

Is it possible ? If yes, how ?

Thanks in advance.

Answer 1

I tried this and the code is working:

from sklearn.feature_selection import SelectFromModel
from sklearn.linear_model import Lasso
from sklearn import preprocessing
dataset = pd.read_csv('Data.csv')
label_encoder = preprocessing.LabelEncoder()
column_list = dataset.columns.tolist()
for i in column_list:
    s = str(dataset[i].dtype)
    if (s == 'object'):
        dataset[i] = label_encoder.fit_transform(dataset[i])
dataset = dataset.dropna()
x = dataset.drop(columns=[Target])
y = dataset[Target].values
estimator = Lasso()
featureselection = SelectFromModel(estimator)
featureselection.fit(x,y)
features = featureselection.transform(x)
x.columns[featureselection.get_support()]

yet, I would like to use KNN Algorithm instead of Lasso().