Data_analysis

Airport survey analysis using Pandas and Sklearn machine learning tools: Random Forest, Support Vector Machines, Decision Tree, KNN, Logistic Regression, Linear SVC, Sthocastic Gradient Descent, Gaussian Naive Bayes and Perceptron.

My goal is to find the best machine learning tool that can predict the variable "Airport Rating" based on other variables.

Basic steps I followed:

1. Survey

• Import survey (.csv file)
• Check data (1400 rows, 47 columns/variables):

2. Data processing

• Data processed using Pandas
• Check correlation between variables:

3. Machine learning models

• Train sklearn maching learning models
• Test models (= predict airport_rating)
• Compare prediction's accuracy:

4. Conclusions

Random Forest is the best model predicting airport_rating with 63% accuracy