Tech ‐ sklearn - yojulab/learn_MLs GitHub Wiki
Quick start
import pandas
from sklearn import linear_model
df = pandas.read_csv("data.csv")
X = df['Weight', 'Volume'](/yojulab/learn_MLs/wiki/'Weight',-'Volume')
y = df['CO2']
regr = linear_model.LinearRegression()
regr.fit(X, y)
predictedCO2 = regr.predict([2300, 1300](/yojulab/learn_MLs/wiki/2300,-1300))
print(predictedCO2)
Beginner
| 분류 | 설명 | 비고 |
|---|---|---|
| regression | multiple_regression | Linear, Polynomial |
| Classfication | DecisionTree, Logistic Regression | youtube-트리 구조 그리기 및 설명 변수 중요도 |
| Clustering | Hierarchical, KNN | -- |
Intermediate
| 분류 | 설명 | 비고 |
|---|---|---|
| preprocessing | Scale, Categorical Data | |
| Modeling | Grid Search, Cross Validation, K-means | |
| Evaluation | Train/Test, Confusion Matrix, AUC - ROC Curve | R2 |
| Bootstrap Aggregation | Bagging |
Advanced
| 분류 | 설명 | 비고 |
|---|---|---|
| Sampling | -- | -- |