https://github.com/ghazaleze/data-mining-fundamentals

my codes of data mining fundamentals course
https://github.com/ghazaleze/data-mining-fundamentals

association-rules classifier clustering data-mining diagram evaluation jupyter-notebook linear-regression mlp-classifier modeling neural-network numpy pandas pca python random-forest skit-learn tree

Last synced: 2 months ago
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my codes of data mining fundamentals course

• Host: GitHub
• URL: https://github.com/ghazaleze/data-mining-fundamentals
• Owner: GhazaleZe
• License: mit
• Created: 2021-02-18T18:36:52.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2021-07-16T15:55:56.000Z (over 3 years ago)
• Last Synced: 2024-01-30T07:46:33.113Z (12 months ago)
• Topics: association-rules, classifier, clustering, data-mining, diagram, evaluation, jupyter-notebook, linear-regression, mlp-classifier, modeling, neural-network, numpy, pandas, pca, python, random-forest, skit-learn, tree
• Language: Jupyter Notebook
• Homepage:
• Size: 2.67 MB
• Stars: 5
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Data Mining Fundamentals

 The codes of my data mining fundamentals course 

## HW1 main topics:

- Start working with pandas and numpy (Q3) 

## HW2 main topics: 

- Preprocessing (Q1)

- Missing Data (Q2, Q3)

- Normalize and Standardization (Q4)

- Outliers (Q5)

- Binnig (Q6)

## HW3 main topics: 

- Summary and visualization (Q1)

- Correlation (Q2)

- Contingency Table (Q3)

- Test and Train (Q4)

- DecisionTreeClassifier with criterion='gini' (Q5)

## HW4 main topics: 

- DecisionTreeClassifier with criterion='entropy' (Q1)

- RandomForestClassifier (Q2)

- confusion_matrix (Q3)

- classification_report (Q3)

## HW5 main topics: 

- Neural Network(MLPClassifier) (Q1)

- Clustering (Q2,Q3)

## HW6 main topics: 

- Linear Regression (Q1, Q2)

- PCA (Q3)

- Association Rule (Q4) 

## HW7 main topics: 

- Logistic Regression (Q1)

- Poisson Regression (Q2)

- Sequence Pattern Mining (Q3)

- Advanced Association Rule Mining (Q4)