language:en size_categories:10M<n<100M format:parquet modality:tabular modality:text library:datasets library:dask library:mlcroissant library:polars region:us finance
---
language:
- en
pretty_name: cs482 Online Ensemble Learning
tags:
- finance
dataset_info:
  features:
  - name: key
    dtype: string
  - name: fare_amount
    dtype: float64
  - name: pickup_datetime
    dtype: string
  - name: pickup_longitude
    dtype: float64
  - name: pickup_latitude
    dtype: float64
  - name: dropoff_longitude
    dtype: float64
  - name: dropoff_latitude
    dtype: float64
  - name: passenger_count
    dtype: int64
  splits:
  - name: train
    num_bytes: 5321378239.727816
    num_examples: 49881470
  - name: test
    num_bytes: 591264296.2721846
    num_examples: 5542386
  download_size: 3775655759
  dataset_size: 5912642536.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---
Created as part of my CS482 Course using data from the [New York City Taxi Fare Kaggle Competition](https://www.kaggle.com/competitions/new-york-city-taxi-fare-prediction/rules).