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mmktech.io

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  • Home
  • Predictive Analytics
    • Back to Basics
    • Correlation
    • Least Square Method
    • Regression – Basics
    • Learn EDA
    • Testing of Hypothesis
  • Feature Selection
    • Filter Methods
      • 1.Variance
      • 2. Correlation based
      • 3 Anova (f Test)
      • 4.Chi-Square
      • 5.Univariate Selection
      • 6.Mutual Information
    • Wrapper Method
      • 1.Forward Selection
      • 2. Backward Elimination
      • 3.Exhaustive Search
    • Embedded Method
      • 1. Decision Tree/RFC
      • 2. Lasso(L1 Regularization)
      • 3. Ridge (L2 Regularization)
    • Hybrid Selection
      • 1.Recursive Elimination
      • 2.Recursive Feature Addition
    • Deep Learning
      • tanH (Hyperbolic Tangent Activation)
  • Regressions
    • Simple Linear Regression
      • Using Excel
      • Using PSPP
      • Using Python-scipy.stats
      • Using statsmodels.api
      • Using Scikit-learn
    • Multiple Linear Regression
      • MLR Problem
      • Using Excel
      • Using Real Statistic Package
      • Using SPSS
      • Using Python
    • Logistic Regression
      • LR Problems
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