GitHub - miriammazzeo95/Machine-Learning-Project: Research on Country Happiness. Machine Learning models, classification and regression, to forecast the level of happiness of a country based on a series of attributes. The overall project aims to address three main tasks: Finding a data set and perform useful transformations in order to prepare the data for analysis, such as filling the missing values and deleting redundant attributes; Analyzing and describing the data using principal component analysis and basic statistic; Solving both a relevant classification and regression problem for the data and statistically evaluate the results.

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.gitattributes		.gitattributes
2019.csv		2019.csv
MiriamMazzeo_MachineLearning_project.pdf		MiriamMazzeo_MachineLearning_project.pdf
assignment2_class_1.py		assignment2_class_1.py
assignment2_class_2.py		assignment2_class_2.py
assignment2_class_stat2.py		assignment2_class_stat2.py
assignment2_part2.py		assignment2_part2.py
assignment2_reg_2.py		assignment2_reg_2.py
assignment2_reg_4.py		assignment2_reg_4.py
assignment2_regression.py		assignment2_regression.py
assignment2_regression_data (1).py		assignment2_regression_data (1).py
assignment2_regression_data.py		assignment2_regression_data.py
countries of the world.csv		countries of the world.csv
country_profile_variables.txt		country_profile_variables.txt
mm_1.py		mm_1.py
mm_2.py		mm_2.py
mm_3.py		mm_3.py
mm_4.py		mm_4.py
mm_5.py		mm_5.py
mm_classification2.py		mm_classification2.py
mm_regressionA.py		mm_regressionA.py
mm_regressionB.py		mm_regressionB.py

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Research on Country Happiness. Machine Learning models, classification and regression, to forecast the level of happiness of a country based on a series of attributes. The overall project aims to address three main tasks: Finding a data set and perform useful transformations in order to prepare the data for analysis, such as filling the missing …