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Category Archives: Machine Learning

Prerequisites: Parametric and Non-Parametric Methods, Hypothesis Testing  In this article, we are going to see how to conduct a Wilcoxon signed-Rank test in the Python… Read More
Artificial Intelligence is a study to make computers, robots, generally, machines think how the intellect of humans works, think, learn when it solves any problem.… Read More
T-score: T-score is defined as the count of standard deviations from the mean data of a t-distribution. In simple words, it is defined as the… Read More
This article focuses on determining the Z-critical value in Python. When we conduct a hypothesis test, we get a test statistic as an outcome. In… Read More
Welch’s t-Test: Two sample t-Test is used to compare the means of two different independent datasets. But we can apply a Two-Sample T-Test on those… Read More
F-critical value is a particular value that we used to compare our f value to. While conducting the F test we obtain F statistics as… Read More
Bartlett’s test is used to check whether all samples have the same variance. it’s also called Bartlett’s test for homogeneity. Before executing some statistical tests… Read More
Dunn’s test should be used to establish which groups are distinct If the Kruskal-Wallis test yields statistically significant findings. After your  ANOVA has revealed a… Read More
Studentized residual is a statistical term and it is defined as the quotient obtained by dividing a residual by its estimated standard deviation. This is… Read More
The p-value in statistics is the likelihood of getting outcomes at least as significant as the observed results of a statistical hypothesis test, given the… Read More
ANCOVA (Analysis of Covariance) is used to identify the statistical difference between means of 2 or more independent groups after controlling one or more explanatory… Read More
When the assumption of equal variances is violated, Welch’s ANOVA is used as an alternative to the standard one-way ANOVA. A one-way ANOVA (“analysis of… Read More
In this article we will undergo basic concepts of the PyBrain package in python,First, we’ll give a brief overview of the function, then discuss its… Read More
SoftmaxLayer executes the softmax distribution from the given input dataset. We can build the network with input, hidden, and output layers using buildNetwork() function and… Read More
In this article, we will be looking at various functionality with the defined examples of the TanhLayer in PyBrain. Layers in Pybrain are functions that… Read More

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