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https://github.com/redtachyon/sklearn-modelling

Predictive modelling of the Adult Data Set (https://archive.ics.uci.edu/ml/datasets/adult)
https://github.com/redtachyon/sklearn-modelling

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Predictive modelling of the Adult Data Set (https://archive.ics.uci.edu/ml/datasets/adult)

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# yazabi-sklearn-project

This repo contains two modules detailed in the assignment: data\_preprocessing.py and train\_and\_test.py, and several convenience modules for training and evaluating models.

Important functions:
- get\_all\_data from train\_and\_test.py allows you to extract all data as a feature matrices.

- run\_search from grid\_search.py allows you to do grid search on a model.

- train\_and\_validate from train\_and\_test.py allows you to train a model and evaluate its performance on the test set

eval\_model.py contains a convenient CLI interface for calling train\_and\_validate. Use it like this: ./eval\_model.py svm -n

Currently supported models:
1. Gaussian Naive Bayes (naive-bayes and naive-bayes-g)
2. Multinomial Naive Bayes (naive-bayes-m) - doesn't support normalized features
3. Bernoulli Naive Bayes (naive-bayes-b)
4. Decision Tree (decision-tree)
5. K Nearest Neighbors (knn)
6. Linear Support Vector Machine (svm)
7. Random Forest (rf)
8. Extra Trees (et)
9. Logistic Regression (logreg)