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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)