Logistic Regression explained

Piya16 Sep, 2020Education

Logistic Regression is one of the machine learning algorithms used for solving classification problems. It is used to estimate probability whether an instance belongs to a class or not. If the estimated probability is greater than threshold, then the model predicts that the instance belongs to that class, or else it predicts that it does not belong to the class as shown in fig 1. This makes it a binary classifier. Logistic regression is used where the value of the dependent variable is 0/1, true/false or yes/no.

Simple linear regression

Piya09 Jun, 2020Education

Simple linear regression is used to find out the best relationship between a single input variable (predictor, independent variable, input feature, input parameter) & output variable (predicted, dependent variable, output feature, output parameter) provided that both variables are continuous in nature. This relationship represents how an input variable is related to the output variable and how it is represented by a straight line.

Correlation vs Covariance

Piya30 May, 2020Education

Correlation and Covariance are two commonly used statistical concepts majorly used to measure the linear relation between two variables in data. When used to compare samples from different populations, covariance is used to identify how two variables vary together whereas correlation is used to determine how change in one variable is affecting the change in another variable. Even though there are certain similarities between these two mathematical terms, these two are different from each other. Read further to understand the difference between covariance and correlation.

data analytics course in Bangalore

Piya14 May, 2020Education

Data analytics is definitely the talk of the town and if you are remotely interested in the Information Technology industry, you might have some idea about it as well. It is the analytics of gathering data, extracting useful information from it and then using these data sets to search for patterns and draw meaningful conclusions. These trends and conclusions are then communicated to the business managers who use these to make informed decisions and ultimately help the company achieve the set prospects and goals. In other words, Data Scientists have an extremely important role in the overall functioning of any organization.

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