Exploratory data analysis: Difference between revisions
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(Created page with "'''Exploratory data analysis (EDA)''' is the first step in the Machine Learning pipeline. It allows us to make informed decisions about tools used to analyze the data. * Look at features of data * Look at correlated features * Find trends and unusual characteristics") |
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* Look at correlated features | * Look at correlated features | ||
* Find trends and unusual characteristics | * Find trends and unusual characteristics | ||
Dataset description | |||
EDA also detects '''unwanted values/noise''' that lead to inaccurate predictions. | |||
EDA finds the correlation of attributes of datasets, such as linearity. | |||
Revision as of 18:16, 3 April 2024
Exploratory data analysis (EDA) is the first step in the Machine Learning pipeline. It allows us to make informed decisions about tools used to analyze the data.
- Look at features of data
- Look at correlated features
- Find trends and unusual characteristics
Dataset description
EDA also detects unwanted values/noise that lead to inaccurate predictions.
EDA finds the correlation of attributes of datasets, such as linearity.
