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Revisions in Logistic Regression R lesson #667

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0bcfd5d
Updated infographics
Vidushi-Gupta Jul 3, 2023
3f68eb4
Changed the problem to finding the white pumpkin
Vidushi-Gupta Jul 3, 2023
51a0024
Removed violin plot
Vidushi-Gupta Jul 3, 2023
f4bc417
Changed orange to white in binary classification
Vidushi-Gupta Jul 3, 2023
a3cd387
Merge branch 'microsoft:main' into main
Vidushi-Gupta Jul 17, 2023
11c780c
Updated the encoding in baked_pumpkins and pumpkins_recipe
Vidushi-Gupta Sep 4, 2023
46d3eb6
Updated evaluation metric values
Vidushi-Gupta Sep 4, 2023
84c4b70
refactored logistic regression r lesson text
jasleen101010 Sep 14, 2023
ab24e44
refactoring logistic regression r text
jasleen101010 Sep 14, 2023
6fddfa5
added categorical plot for pumpkin colors variety
jasleen101010 Sep 14, 2023
9054bad
Merge branch 'main' of https://github.com/jasleen101010/ML-For-Beginners
jasleen101010 Sep 14, 2023
435f1ed
removed box plot and added cat plot
jasleen101010 Sep 16, 2023
8b7d50a
added plot for relationship bw features and labels
jasleen101010 Sep 16, 2023
f0f2065
fixed spacing and variables in plots
jasleen101010 Sep 16, 2023
81db2c8
fixed spacing
jasleen101010 Sep 16, 2023
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refactored text
jasleen101010 Sep 16, 2023
066bf89
fixed plot and modelling error
jasleen101010 Sep 19, 2023
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knitted html file
jasleen101010 Sep 19, 2023
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knitted lesson_4-R.ipynb
jasleen101010 Sep 19, 2023
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Merge pull request #1 from jasleen101010/main
Vidushi-Gupta Sep 19, 2023
91ad229
Fixing image path
carlotta94c Sep 25, 2023
84043d8
Fixing image path
carlotta94c Sep 25, 2023
72de468
Reviewing lesson_4-R.ipynb
carlotta94c Sep 25, 2023
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Fixing image path
carlotta94c Sep 25, 2023
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updated the html and rmd files from ipynb file
jasleen101010 Sep 25, 2023
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Merge pull request #2 from jasleen101010/main
Vidushi-Gupta Sep 25, 2023
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2 changes: 1 addition & 1 deletion 2-Regression/4-Logistic/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ Logistic regression differs from linear regression, which you learned about prev

### Binary classification

Logistic regression does not offer the same features as linear regression. The former offers a prediction about a binary category ("orange or not orange") whereas the latter is capable of predicting continual values, for example given the origin of a pumpkin and the time of harvest, _how much its price will rise_.
Logistic regression does not offer the same features as linear regression. The former offers a prediction about a binary category ("white or not white") whereas the latter is capable of predicting continual values, for example given the origin of a pumpkin and the time of harvest, _how much its price will rise_.

![Pumpkin classification Model](./images/pumpkin-classifier.png)
> Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded)
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