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)