Use case on the OnlineNewsPopularity dataset

Dataset OnlineNewsPopularity

Machine Learning Task: Regression

This is an Online News Popularity database. This dataset summarizes a heterogeneous set of features about Mashable articles in a period of two years. The goal is to predict the number of shares in social networks (popularity).

Available at OpenML:

Category: Marketing

# Rows: 39,644 # Columns: 60

Target: shares


Numeric: timedelta, n_tokens_title, n_tokens_content, n_unique_tokens, n_non_stop_words, n_non_stop_unique_tokens, num_hrefs, num_self_hrefs, num_imgs, num_videos, average_token_length, num_keywords, data_channel_is_lifestyle, data_channel_is_entertainment, data_channel_is_bus, data_channel_is_socmed, data_channel_is_tech, data_channel_is_world, kw_min_min, kw_max_min, ...

Nominal: url

Machine Learning Use Case Marketing

Root Mean Square Error (RMSE)

Onlinenewspopularity Rmse

Mean Absolute Error (MAE)

Onlinenewspopularity Mae

Coefficient of Determination (R2)

Onlinenewspopularity R2

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