Model Metrics – Introduction to Text Analytics with R Part 9

Model Metrics includes specific coverage of:

– The importance of metrics beyond accuracy for building effective models.
– Coverage of sensitivity and specificity and their importance for building effective binary classification models.
– The importance of feature engineering for building the most effective models.
– How to identify if an engineered feature is likely to be effective in Production.
– Improving our model with an engineered feature.

Kaggle Dataset:
Kaggle Spam Data Set

The data and R code here

Full Series:
Introduction to Text Analytics with R

More Data Science Material:
[Video] Classification Models
[Blog]  Machine Learning As A Service Tutorial: Deploy the Models!




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- Data Science Dojo is a paradigm shift in data science learning. We enable all professionals (and students) to extract actionable insights from data.


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