Bowles_2.4_abalone: Real‐Valued Predictions with Factor Variables: How Old Is Your Abalone?
Listing 2-11: Read and Summarize the Abalone Data Set—abaloneSummary.py
- pd.read_csv(target_url,header=None, prefix="V")
- abalone.columns = ['Sex', 'Length', 'Diameter', 'Height', 'Whole weight','Shucked weight', 'Viscera weight', 'Shell weight', 'Rings']
Listing 2-12: Parallel Coordinate Plot for Abalone Data—abaloneParallelPlot.py
Equation 2-5: Using logit transform for soft range compression
Listing 2-13: Correlation Calculations for Abalone Data—abaloneCorrHeat.py
ipynb: $anaconda/ipynb-tasks/bowles/Bowles_2.4_abalone.ipynb