What are precision and recall in machine learning? In a classification problem, precision and recall are two metrics using which we can measure the performance of the machine learning model. We know that: True Positives (TP): True positives are those output labels...

What is the accuracy score in machine learning? In the case of classification problems, accuracy is a metric using which the performance of the machine learning model can be measured. In this article, we will discuss what accuracy in machine learning is and how we can...

What is the Confusion Matrix? Let’s say we have some features in a dataset. We have the petal length, petal width, sepal length, and sepal width of a flower. And based on these features we need to classify the type of flower. If the output is True, the flower is of...

What is R-squared in machine learning? Let’s say a machine learning model gives the following output: [y1, y2, …, yn] And the actual output or the expected output is the following: [ya1, ya2, ya3, … yan] So, the error, in this case, is $latex e_{i}=y_{i}-y_{ai} \quad...

What is the Mean Absolute Error (MAE)? Let’s say we created a linear regression model. The expected output of the model is: [ya1, ya2, ya3, … yan] And the model gave the following output: [y1, y2, …, yn] The Mean Absolute Error (MAE) is the average of absolute error...