ML 스터디 14주차 과제 #31

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Open

whitesoil opened this issue Jan 7, 2019 · 0 comments

Member

whitesoil commented Jan 7, 2019 •

edited

Loading

Week 14 : Confusion Matrix / Standardization, Normalization, Regularization / Data Preprocessing

기한 : 1월 14일

정초이

Confusion Matrix

True Positives
False Negatives
False Positives
True Negatives
Error, Accuracy
True Positive Rate, False Positive Rate
Precision, Recall
F1-score
The Scoring metrics for multiclass classification

남궁선

Data Preprocessing

Missing data
Categorical data
Unbalanced data set
Multicollinearity
Outlier
Date scaling

조민지

Mathmatics

Standardization
Normalization
- Batch Normalization
Regularization
- L1 Regularization
- L2 Regularization

수식과 그 의미 그리고 활용법이 가장 중요합니다.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment