This content originally appeared on DEV Community and was authored by Durga Pokharel
Despite of being women from non-technical background, I was able to complete my 100s days as learning new things and most of the time not knowing what am I doing. But its looking back at the first day when I was feeling confused about naming the variable, I am feeling like I know something now. Also, I have just applied for an intern position.
This is my 100th day of #100daysofcode and #python learning journey. Like usual day todays also I keep learning from DataCamp. I completed some assignments there.
Code for Regression with categorical features
# Import necessary modules
from sklearn.model_selection import cross_val_score
from sklearn.linear_model import Ridge
# Instantiate a ridge regressor: ridge
ridge = Ridge(alpha=0.5, normalize=True)
# Perform 5-fold cross-validation: ridge_cv
ridge_cv = cross_val_score(ridge, X, y, cv=5)
# Print the cross-validated scores
print(ridge_cv)
Output of the above code will be
[0.86808336 0.80623545 0.84004203 0.7754344 0.87503712]
Day 100 Of #100DaysOfCode and #Python
— Durga Pokharel (@durgacodes) April 8, 2021
Regression with categorical features from DataCamp#WomenWhoCode #100DaysOfCode #CodeNewbie #DEVCommunity pic.twitter.com/mrYnm1EfSc
This content originally appeared on DEV Community and was authored by Durga Pokharel
Durga Pokharel | Sciencx (2021-04-08T17:24:06+00:00) Day 100 Of 100DaysOfCode: Regression with categorical features. Retrieved from https://www.scien.cx/2021/04/08/day-100-of-100daysofcode-regression-with-categorical-features/
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