import pandas as pd
import numpy as np
import os

import matplotlib.pyplot as plt
import plotly.express as px
import plotly.graph_objects as go
pd.options.plotting.backend = 'plotly'
TEMPLATE = 'seaborn'

import warnings
warnings.simplefilter('ignore')

Lecture 25 – Grid Search, Multicollinearity, Examples

DSC 80, Winter 2023

Announcements

• Lab 9 (pipelines) is due today at 11:59PM.
• Project 5 (prediction) is due on Thursday, March 23rd at 11:59PM (no slip days allowed)!
• There is no live lecture on Wednesday or Friday; videos for these lectures have already been posted on the course website.
  • There is still discussion on Wednesday.
• The Final Exam is on Wednesday, March 22nd from 11:30AM-2:30PM, location TBD.
  • Lectures 1-26 (everything before this Friday) are in scope, as are all assignments.
  • You can bring 2 two-sided notes sheets. More details to come on Ed.
  • practice.dsc80.com now contains 3 past finals. Start reviewing!

• If at least 80% of the class fills out BOTH CAPEs and the End-of-Quarter Survey, then everyone will receive an extra 0.5% added to their overall course grade.

  • Deadline: Saturday, March 18th at 8AM.

• Look at this Ed post for a description of the difference between parameters and hyperparameters.

Agenda

• Recap: Decision trees 🌲 and grid search.
• Multicollinearity (including how it arises in one hot encoding).
• Example: Modeling with text features.

Recap: Decision trees 🌲 and grid search

Example: Predicting diabetes

diabetes = pd.read_csv('data/diabetes.csv')
diabetes.head()

	Pregnancies	Glucose	BloodPressure	SkinThickness	Insulin	BMI	DiabetesPedigreeFunction	Age	Outcome
0	6	148	72	35	0	33.6	0.627	50	1
1	1	85	66	29	0	26.6	0.351	31	0
2	8	183	64	0	0	23.3	0.672	32	1
3	1	89	66	23	94	28.1	0.167	21	0
4	0	137	40	35	168	43.1	2.288	33	1

fig = (
    diabetes.assign(Outcome=diabetes['Outcome'].astype(str))
            .plot(kind='scatter', x='Glucose', y='BMI', color='Outcome', 
                  color_discrete_map={'0': 'orange', '1': 'blue'},
                  title='Relationship between Glucose, BMI, and Diabetes',
                  template=TEMPLATE)
)
fig