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Fun with Numbers: Detective Techniques
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Module 10
The Mystery Client
1
KNN for Client Classification
Classify a new client by applying the K-Nearest Neighbors (KNN) algorithm to their profile data.
2
Naive Bayes Classification with Mixed Features
Re-classify the client using a Naive Bayes model, handling both discrete and continuous (Gaussian) features appropriately.
3
Building Decision Trees: Gini Impurity & Information Gain
Construct a two-level decision tree profile for the client by identifying the most informative features using Gini impurity or information gain.
4
Synthesizing Classifications for Client Identification
Compare the classifications from all three models (KNN, Naive Bayes, Decision Tree) to reach a final conclusion about the mystery client's identity.
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The Anonymous Saboteur
Next module
The Boutique's Inventory Heist