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  • 1. Introduction
  • 2. Machine Learning
    • 2.1 Linear Regression
      • 2.1.1 Least-squares method
      • 2.1.2 Ridge and Lasso regression
      • 2.1.3 Outliers and Robustness
    • 2.2 Linear Classification
      • 2.2.1 Logistic Regression
      • 2.2.2 Linear Discriminant Analysis
    • 2.3 Decision Tree
      • 2.3.1 Decision Tree (Classification)
      • 2.3.2 Decision tree (regression)
      • 2.3.3 Decision Tree Parameters
    • 2.4 Ensemble
      • 2.4.1 Random Forests
      • 2.4.2 Stacking
      • 2.4.3 Adaboost (classification)
      • 2.4.4 Adaboost(Regression)
      • 2.4.5 Gradient boosting
    • 2.5 Clustering
      • 2.5.1 k-means
      • 2.5.2 k-means++
      • 2.5.3 X-means
    • 2.6 Dimensionality Reduction
      • 2.6.1 PCA
      • 2.6.2 SVD
    • 2.7 Feature Selection
    • 2.8Time Series
      • 2.8.1 Using Prophet
    • 2.9 Anomaly detection
      • 2.9.1 Anomaly Detection ①
      • 2.9.2Anomaly Detection②
  • 3. Preprocess
    • 3.1 Numerical Data
      • 3.3.1 Binning
      • 3.3.2 BoxCox transformation
      • 3.3.3 YeoJonson transformation
    • 3.2 Categorical Data
    • 3.3 Table
    • 3.4 Others
  • 4. Metrics
    • 4.1 Model Selection
    • 4.2 Regression
      • 4.2.1 Correlation coefficient
      • 4.2.2 Coefficient of determination
    • 4.3 Classification
      • 4.3.1 ROC-AUC
  • 5. TimeSeries
    • 5.1 Plotting and Preprocessing
      • 5.1.1 Check Dataset
      • 5.1.2 Impact of Trends
      • 5.1.3 Trend & Periodicity
      • 5.1.4 Box-Cox transformation
      • 5.1.5 Adjustment
    • 5.2 Exponential smoothing
    • 5.3 Univariate
      • 5.3.5 AR Process
      • 5.3.6 MA Process
    • 5.4 Multi-variate
    • 5.5 Shape & Similarity
      • 5.5.1 Dynamic Time Warping
    • 5.6 timeseries forecast
    • 5.7 Hierarchical and Grouped Time Series
  • 6. Visualization
    • 6.1 Numeric Value Distribution
      • 6.1.1 Map of Japan
      • 6.1.2 Tree map
      • 6.1.3 Doughnut chart
      • 6.1.4 Sankey Diagram
    • 6.2 Category & Number
      • 6.2.1 Histogram
      • 6.2.2 Density plot
      • 6.2.3 Ridgeline plot
      • 6.2.4 Violin plot
    • Appendix
  • 7. Economic Data
    • 7.1 Time Series
      • 7.1.1 FRED
      • 7.1.2 mplfinance
    • 7.2 Visualize
      • 7.2.1 Country risk premium
      • 7.2.2 positive and negative changes
      • 7.2.3 Radar chart
    • 7.3 NLP
      • 7.3.1 Sentiment analysis of text
    • Issues
    • Privacy Policy
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