-
Notifications
You must be signed in to change notification settings - Fork 274
Problems
[binary-classification] [classification] [ensembling] [gradient_boosting] [hierarchical-data] [k-nearest-neighbors] [logistic-regression] [multi-class-classification] [multi-level-data] [naive-bayes] [NLP] [one-hot-encoding] [python] [R] [random-forest] [rank-target] [regression] [sparse-data] [stacking] [supervised-learning] [support-vector-machine] [text-classification] [xgboost]
Four people throw darts at a dart board. Use the location of labelled darts to predict who threw the unlabelled ones.
[classification] [ensembling] [k-nearest-neighbors] [logistic-regression] [multi-class-classification] [R] [stacking] [supervised-learning] [support-vector-machine]
Predict the species of an iris flower (setosa, verginica, or versicolor) given some of its properties.
[classification] [gradient_boosting] [multi-class-classification] [R] [supervised-learning] [xgboost]
Given a job title like "junior data analyst" categorize it as one of "finance", "sales", or "technology".
[classification] [multi-class-classification] [naive-bayes] [NLP] [one-hot-encoding] [python] [R] [sparse-data] [supervised-learning] [text-classification]
Predict the average income of a person given his city, region, and country.
[gradient_boosting] [hierarchical-data] [multi-level-data] [one-hot-encoding] [R] [regression] [sparse-data] [supervised-learning] [xgboost]
Predict wether the New Orleans Saints will win a football game against their opponent using fictitious data on historical Saints games.
[binary-classification] [classification] [python] [R] [random-forest] [supervised-learning]
Given a set of sales leads (i.e. prospective customers), rank which ones will most likely convert to a sale.
[binary-classification] [classification] [gradient_boosting] [logistic-regression] [one-hot-encoding] [python] [R] [random-forest] [rank-target] [sparse-data] [supervised-learning] [xgboost]