Month: March 2021

bias and variance

Bias and Variance

Bias and Variance Introduction Machine learning models are developed primarily to produce good predictions for some desired quantity. What we want is a model that can generalise well the patterns in our data in order to make reasonable predictions. Two important measures of how well a model generalises are bias and variance: Bias is the tendency …

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mean absolute error

Mean Absolute Error

Mean Absolute Error Introduction With any machine learning project, it is essential to measure the performance of the model. What we need is a metric to quantify the prediction error in a way that is easily understandable to an audience without a strong technical background. For regression problems, the Mean Absolute Error (MAE) is just such …

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