jlroviramartin / proyectokaggle

Proyecto del Máster de IA para el dataset de Kobe Bryant

ProyectoKaggle

Proyecto del Máster de IA para el dataset de Kobe Bryant

Instrucciones

EJERCICIO Selección de variables

Entrega una memoria (de 10 páginas como máximo) describiendo el proceso realizado en cada una de las fases (preprocesado de datos, modelado y validación) del proyecto realizado en la plataforma Kaggle.

En la documentación dispones de toda la información.

Data Description

This data contains the location and circumstances of every field goal attempted by Kobe Bryant took during his 20-year career. Your task is to predict whether the basket went in (shot_made_flag).

We have removed 5000 of the shot_made_flags (represented as missing values in the csv file). These are the test set shots for which you must submit a prediction. You are provided a sample submission file with the correct shot_ids needed for a valid prediction.

To avoid leakage, your method should only train on events that occurred prior to the shot for which you are predicting! Since this is a playground competition with public answers, it's up to you to abide by this rule.

The field names are self explanatory and contain the following attributes:

action_type
combined_shot_type
game_event_id
game_id
lat
loc_x
loc_y
lon
minutes_remaining
period
playoffs
season 
seconds_remaining
shot_distance
shot_made_flag (this is what you are predicting)
shot_type
shot_zone_area
shot_zone_basic
shot_zone_range
team_id
team_name
game_date
matchup
opponent
shot_id