Kaggle Housing Prices Competition Link
Objective: Predict the sales price of individual residential property in Ames, Iowa from 2006 to 2010. For each Id in the test set, a prediction value should be populated for the SalePrice variable.
Notes on Submissions:
-
first-submission.csv
- Algorithm: Random Forests
- Features:
['LotArea', 'YearBuilt', '1stFlrSF', '2ndFlrSF', 'FullBath', 'BedroomAbvGr', 'TotRmsAbvGrd']
- Root-Mean-Squared-Error (RMSE) score: 22337.06
-
second-submission.csv
- Algorithm: Gradient Boosting Regression
- Features: All table variables
- Used Hyperparameter Tuning - GridSearchCV
- Root-Mean-Squared-Error (RMSE) score: 182906.48
-
third-submission.csv
- Algorithm: Gradient Boosting Regression
- Features:
['LotArea', 'YearBuilt', '1stFlrSF', '2ndFlrSF', 'FullBath', 'BedroomAbvGr', 'TotRmsAbvGrd']
- Used Hyperparameter Tuning - GridSearchCV
- Root-Mean-Squared-Error (RMSE) score: 182906.48
-
fourth-submission.csv
- Algorithm: Linear Regression
- Features:
['MSSubClass', 'LotFrontage', 'LotArea', 'OverallQual', 'OverallCond', 'YearBuilt', 'YearRemodAdd', 'MasVnrArea', 'BsmtFinSF1', 'BsmtUnfSF', 'TotalBsmtSF', '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'FullBath', 'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr', 'TotRmsAbvGrd', 'Fireplaces', 'GarageCars', 'WoodDeckSF', 'OpenPorchSF', 'EnclosedPorch', 'ScreenPorch', 'PoolArea']
- Root-Mean-Squared-Error (RMSE) score: 20476.40
Kaggle Titanic Competition Link
Objective: Use machine learning to create a model that predicts which passengers survived the Titanic shipwreck by using passenger data (ie name, age, gender, socio-economic class, etc).
Notes on Submissions:
-
first-submission.csv
- Algorithm: Random Forests
- Features:
['Pclass', 'Sex', 'SibSp', 'Parch']
- Categorization accuracy score: 0.59569
-
second-submission.csv
- Algorithm: Random Forests
- Features:
['Pclass', 'Sex', 'SibSp', 'Parch']
- Used Hyperparameter Tuning - GridSearchCV
- Categorization accuracy score: 0.76555
-
third-submission.csv
- Algorithm: Logistic Regression
- Features:
['Pclass', 'Sex', 'SibSp', 'Parch']
- Used Hyperparameter Tuning - GridSearchCV
- Categorization accuracy score: 0.77511
-
fourth-submission.csv
- Algorithm: Random Forests
- Features:
['Pclass','Sex','Age','Fare','Family_cnt','Cabin_ind']
- Used Hyperparameter Tuning - GridSearchCV
- Categorization accuracy score: 0.78708