The coefficient of determination (also depicted as R^2) is a calculation of the proportion of the variance in the dependent variable (noted as y) which is explained by a linear regression model. The value of the coefficient of determination can be in the 0..1 range. The coefficient of determination can be calculated by using the ... Read more
In machine learning, normalization is a statistical technique by which the data in a dataset are transformed to have values in a normal (Gaussian) distribution. For each value x in the dataset, its corresponding normalized value x' is calculated in the value range [0,1] as follows. Alternatively, there can be a mean normalization, with normalized ... Read more
A standard deviation (or σ) is a statistical metric (measure) of how dispersed the data is in relation to the mean. It if frequently used in machine learning data preparation and in machine learning model training.
