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open Graph Image
photo
open Graph Image
photo
is In Organization
No
is In Organization
Yes
description
This project looks at the effectiveness of SICE imputation technique in supporting binary classification performance of the Logisitic Regression in the context of decision support for the healthcare sector where accurate predictive models have the potential to improve patient outcomes by promoting access to care. Processing methodologies are assesed with reference to the relevant Accuracy and False Positive metrics. Analysis and comparison of the results suggest that imputation alone can likely impact classifier performance only marginally in situations where the data set is of sufficient size.
description
Promise based HTTP client for the browser and node.js
homepage
homepage
https://axios-http.com
url
https://githubhelp/smjajoo/pima-data-modeling-and-analysis
url
https://githubhelp/axios/axios
disk Usage
24
dis kUsage
14936
stargazer Count
0
stargazer Count
104549
forkCount
0
forkCount
10760
watcher Count
1
watcher Count
1201
created At
2022-06-29
created At
2014-08-19
license Info
license Info
MIT License
issues
0
issues
50
languages
1
languages
4
repository Topics
0
repository Topics
5
owner
smjajoo
owner
axios
owner Avatar
photo
owner Avatar
photo
other
other

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