Package com.leumanuel.woozydata.service

Class RegressionService

java.lang.Object
com.leumanuel.woozydata.service.RegressionService
public class RegressionService extends Object
Service class for regression analysis and correlation calculations. Provides methods for various types of regression models and statistical correlations.
Version:
1.0
Author:
Leu A. Manuel

  • Constructor Details

    • RegressionService

      public RegressionService()

  • Method Details

    • calculatePearsonCorrelation

      public double calculatePearsonCorrelation(DataFrame dataFrame, String column1, String column2)
      Calculates Pearson correlation coefficient between two columns.
      Parameters:
      dataFrame - DataFrame containing the data
      column1 - Name of first column
      column2 - Name of second column
      Returns:
      Pearson correlation coefficient
      Throws:
      IllegalArgumentException - if columns are not numeric

    • simpleLinearRegression

      public double[] simpleLinearRegression(DataFrame dataFrame, String xColumn, String yColumn)
      Performs simple linear regression between two columns. Returns array containing [slope, intercept].
      Parameters:
      dataFrame - DataFrame containing the data
      xColumn - Independent variable column name
      yColumn - Dependent variable column name
      Returns:
      double array where [0] = slope, [1] = intercept
      Throws:
      IllegalArgumentException - if columns are not numeric

    • calculateRSquared

      public double calculateRSquared(DataFrame df, String xCol, String yCol)
      Calculates R-squared (coefficient of determination) for linear regression.
      Parameters:
      df - DataFrame containing the data
      xCol - Independent variable column name
      yCol - Dependent variable column name
      Returns:
      R-squared value
      Throws:
      IllegalArgumentException - if columns are not numeric

    • multipleRegression

      public DataFrame multipleRegression(DataFrame df, String[] xCols, String yCol)
      Performs multiple linear regression analysis.
      Parameters:
      df - DataFrame containing the data
      xCols - Array of independent variable column names
      yCol - Dependent variable column name
      Returns:
      DataFrame containing regression coefficients
      Throws:
      IllegalArgumentException - if any column is not numeric

    • polynomialRegression

      public DataFrame polynomialRegression(DataFrame df, String xCol, String yCol, int degree)
      Performs polynomial regression analysis.
      Parameters:
      df - DataFrame containing the data
      xCol - Independent variable column name
      yCol - Dependent variable column name
      degree - Degree of polynomial
      Returns:
      DataFrame containing polynomial coefficients
      Throws:
      IllegalArgumentException - if columns are not numeric or degree is invalid

    • logisticRegression

      public DataFrame logisticRegression(DataFrame df, String xCol, String yCol)
      Performs logistic regression analysis for binary classification.
      Parameters:
      df - DataFrame containing the data
      xCol - Independent variable column name
      yCol - Dependent variable column name (should contain binary values)
      Returns:
      DataFrame containing logistic regression coefficients
      Throws:
      IllegalArgumentException - if columns are not numeric or y is not binary