Mushroom hunting (otherwise known as "shrooming") - kaggle
Edible or poisonous
Your task is to move the sliders under the model chart and view the effect on prediction accuracy.
(Hint: it is really easy to achieve 100% accuracy, the purpose is to explore how changing
the different model parameters affect training and validation.)
- The model uses XGBoost algorithm to predict if a mushroom is edible or poisonous.
- The baseline is based on the most frequent feature in the training set.
- Top 10 features are listed to the right of the chart.
- The data is sourced from the UCI Machine Learning repository.
(If your chart appears compressed, try resizing the browser window to knock it back into shape!)