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  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series .

  3. Lift (data mining) - Wikipedia

    en.wikipedia.org/wiki/Lift_(data_mining)

    In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model.

  4. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).

  5. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    Another issue is the robustness to outliers, to which sample covariance matrices are highly sensitive. [ 2 ] [ 3 ] [ 4 ] Statistical analyses of multivariate data often involve exploratory studies of the way in which the variables change in relation to one another and this may be followed up by explicit statistical models involving the ...

  6. Ordinary least squares - Wikipedia

    en.wikipedia.org/wiki/Ordinary_least_squares

    In statistics, ordinary least squares (OLS) is a type of linear least squares method for choosing the unknown parameters in a linear regression model (with fixed level-one [clarification needed] effects of a linear function of a set of explanatory variables) by the principle of least squares: minimizing the sum of the squares of the differences between the observed dependent variable (values ...

  7. Bessel's correction - Wikipedia

    en.wikipedia.org/wiki/Bessel's_correction

    The sum of the entries in the middle column must be zero because the term a will be added across all 5 rows, which itself must equal zero. That is because a contains the 5 individual samples (left side within parentheses) which – when added – naturally have the same sum as adding 5 times the sample mean of those 5 numbers (2052).

  8. Subtractor - Wikipedia

    en.wikipedia.org/wiki/Subtractor

    Figure 1: Logic diagram for a half subtractor. The half subtractors can be designed through the combinational Boolean logic circuits [2] as shown in Figure 1 and 2. The half subtractor is a combinational circuit which is used to perform subtraction of two bits.

  9. Softmax function - Wikipedia

    en.wikipedia.org/wiki/Softmax_function

    One can normalize input scores by assuming that the sum is zero (subtract the average: where =), and then the softmax takes the hyperplane of points that sum to zero, =, to the open simplex of positive values that sum to 1 =, analogously to how the exponent takes 0 to 1, = and is positive.