Hello,

I want to build a classification algorithm for my machine learning class so i need to find a (nonpopular) dataset that is somewhat contaminated so i can apply data preperation methods as the assignment requires. Do you guys have anything that you can recommend to me ?

Thanks in advance.

PS. There are datasets that i am not allowed to use you can see them below.

Please DO NOT use these datasets in your projects! [http://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength](http://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength) [http://yann.lecun.com/exdb/mnist/](http://yann.lecun.com/exdb/mnist/) [https://archive.ics.uci.edu/ml/datasets/bank+marketing](https://archive.ics.uci.edu/ml/datasets/bank+marketing) [https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29](https://archive.ics.uci.edu/ml/datasets/Breast+Cancer+Wisconsin+%28Diagnostic%29) [https://archive.ics.uci.edu/ml/datasets/car+evaluation](https://archive.ics.uci.edu/ml/datasets/car+evaluation) [https://archive.ics.uci.edu/ml/datasets/census+income](https://archive.ics.uci.edu/ml/datasets/census+income) [https://archive.ics.uci.edu/ml/datasets/Covertype](https://archive.ics.uci.edu/ml/datasets/Covertype) [https://archive.ics.uci.edu/ml/datasets/Mushroom](https://archive.ics.uci.edu/ml/datasets/Mushroom) [https://archive.ics.uci.edu/ml/datasets/Online+News+Popularity](https://archive.ics.uci.edu/ml/datasets/Online+News+Popularity)) [https://archive.ics.uci.edu/ml/datasets/Online+Shoppers+Purchasing+Intention+Dataset](https://archive.ics.uci.edu/ml/datasets/Online+Shoppers+Purchasing+Intention+Dataset) [https://data.world/exercises/logistic-regression-exercise-1/workspace/file?filename=nba\_logreg.csv](https://data.world/exercises/logistic-regression-exercise-1/workspace/file?filename=nba_logreg.csv) [https://github.com/nrkfeller/machinelearningnotes/blob/master/breast-cancer-wisconsin.data.txt](https://github.com/nrkfeller/machinelearningnotes/blob/master/breast-cancer-wisconsin.data.txt) [https://github.com/ozgurshn/TurkishBanknoteDataset](https://github.com/ozgurshn/TurkishBanknoteDataset) [https://github.com/stedy/Machine-Learning-with-R-datasets/blob/master/whitewines.csv](https://github.com/stedy/Machine-Learning-with-R-datasets/blob/master/whitewines.csv) [https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/diabetes.csv](https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/diabetes.csv) [https://kaggle.com/harlfoxem/housesalesprediction](https://kaggle.com/harlfoxem/housesalesprediction) [https://www.kaggle.com/chirin/africa-economic-banking-and-systemic-crisis-data](https://www.kaggle.com/chirin/africa-economic-banking-and-systemic-crisis-data) [https://www.kaggle.com/datasnaek/league-of-legends](https://www.kaggle.com/datasnaek/league-of-legends) [https://www.kaggle.com/dronio/SolarEnergy](https://www.kaggle.com/dronio/SolarEnergy) [https://www.kaggle.com/geomack/spotifyclassification](https://www.kaggle.com/geomack/spotifyclassification) [https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results#athlete\_events.csv](https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results#athlete_events.csv) [https://www.kaggle.com/jsphyg/weather-dataset-rattle-package](https://www.kaggle.com/jsphyg/weather-dataset-rattle-package) [https://www.kaggle.com/keplersmachines/kepler-labelled-time-series-data](https://www.kaggle.com/keplersmachines/kepler-labelled-time-series-data) [https://www.kaggle.com/marcelotc/german-credit-risk](https://www.kaggle.com/marcelotc/german-credit-risk) [https://www.kaggle.com/mlg-ulb/creditcardfraud](https://www.kaggle.com/mlg-ulb/creditcardfraud) [https://www.kaggle.com/primaryobjects/voicegender](https://www.kaggle.com/primaryobjects/voicegender) [https://www.kaggle.com/shivam2503/diamonds](https://www.kaggle.com/shivam2503/diamonds) [https://www.kaggle.com/shrutimechlearn/churn-modelling](https://www.kaggle.com/shrutimechlearn/churn-modelling) [https://www.kaggle.com/spscientist/students-performance-in-exams](https://www.kaggle.com/spscientist/students-performance-in-exams) [https://www.kaggle.com/tmdb/tmdb-movie-metadata#tmdb\_5000\_movies.csv](https://www.kaggle.com/tmdb/tmdb-movie-metadata#tmdb_5000_movies.csv)