erleholgersen / eprate

Predictive modelling of IMDb TV episode ratings based on episode description

eprate

Text mining of IMDB episode descriptions to look for associations with episode rating.

The scripts are written in Python 3, and depend on numpy, pandas, scikit-learn and the IMDbPy module.

Downloading Data

To download data, run the gather_data.py script. The script takes the name of the show as a command line argument.

$ python3 gather_data.py "Doctor Who"
Downloading data on Doctor Who

Predicting on New Data

To predict the rating for a new episode description, use the predict_rating.py script. The prediction is made based on a gradient boosting machine with 100 iterations and a learning rate of 0.01.

$ python3 predict_rating.py "Doctor Who" "The Doctor adopts a baby Dalek"
[ 8.10292221]

Benchmarking Models

The script benchmark_models.py can be used to assess the performance of different algorithms on predicting ratings for a particular show through h2o. The h2o leaderboard is printed to screen.

$ python3 benchmark_models.py "Doctor Who"

Visualization

In addition to the main Python scripts, there is an R script make_plots.R for visualization. Examples of the output are shown below.

Doctor Who

The West Wing

Game of Thrones