ahmadmardeni1
commented
3 years ago Thank you for submitting your topic. @Muthami-John After some careful consideration, it struck us that this topic may be a bit over-saturated throughout other blog sites and official documentation.
We believe this is the best way for students to build a great portfolio (for potential employers) is by building what does not exist and what can provide the most value.
Please feel free to suggest an alternate topic to explore. 🚀
Topic Suggestion
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Proposal Submission
Implementing a Logistic Regression in R
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Proposed article introduction
Logistic regression is a machine learning classifier that is used in both binary and multi-class classification tasks. This algorithm uses a sigmoid function to transform a linear function such that the predicted output is a probability and thus falls between 0 and 1. In the real world, this algorithm is widely applied in many scientific fields. For instance, in medicine, it's used to classify a tumour as malignant or benign. It's also used to determine whether transactions are fraudulent or not. In the Natural language, this algorithm is used to determine the sentiment of movie reviews. These are but a few examples of real-world applications of logistic regression.
In this article, we shall introduce the underlined principles behind the logistic regression and, using tabular data, show how we can implement and use our model to make predictions in R.
Key takeaways
By the end of this session, the reader will know:
Article quality
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Conclusion
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