Logistic Regression
- By
Wayne
Logistic regression is a data analysis technique used for classification. It is probably the simplest model among classification algorithms.
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Machine Learning
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Logistic Regression
- By
Logistic regression is a data analysis technique used for classification. It is probably the simplest model among classification algorithms.
Linear Regression
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Linear regression is a data analysis technique that uses linear functions to predict data. Although the linear regression model is relatively simple, it is a mature statistical technique.
Regularization
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When a model has poor performance, it cannot predict the data accurately. The main cause may be overfitting or underfitting. If it is a case of overfitting, we can use regularization to solve model overfitting.
Overfitting and Underfitting
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Overfitting and underfitting are the root causes for poor model accuracy. Only by being able to determine whether a model is overfitting or underfitting can we take the correct approach to improve the performance of the model.
Feature Scaling
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In machine learning, before we take the data to train a model, we usually need to perform feature scaling on the data.
Confusion Matrix
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The confusion matrix is a tool used to measure the performances of models. This allows data scientists to analyze and optimize models. Therefore, when learning machine learning, we must learn to use confusion matrix. In addition, this article will also introduce accuracy, recall, precision, and F1 score.
SciPy Spearman Correlation Coefficient
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Spearman Correlation Coefficient is a nonparametric method. It calculates the ranks by sorting the two variables, and then calculates the difference between the ranks to measure the correlation between the two variables.
SciPy Mann-Whitney U Test
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Mann-Whitney U test is a nonparametric test. It combines the two samples, sort them, and assign them ranks according to the orders to test if the distribution of two population are equal.
SciPy Chi-Square Test
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Chi-Square Test tests whether the variables in a crosstab are independent based on the observed frequencies. SciPy’s chi2_contingency() can help us quickly calculate chi-square statistic and p-value.
