Introduction to Naïve Bayes Algorithm in Machine Learning The Naïve Bayes algorithm is a classification algorithm that is based on the Bayes Theorem, such that it assumes all the predictors are independent of each other. Basically, it is a probability-based machine learning classification algorithm which tends out to be highlyContinue Reading
Introduction to Decision Trees Decision trees are one of the most powerful classification algorithm that falls under supervised learning-based algorithms. It is used as a tool for making predictions and can be incorporated in different fields. With the help of decision trees, the data-set can be divided in different waysContinue Reading
Support Vector Machines are part of the supervised learning model with an associated learning algorithm. It is the most powerful and flexible algorithm used for classification, regression, and detection of outliers. It is used in case of high dimension spaces, where each data item is plotted as a point inContinue Reading
The Logistic regression model is a supervised learning model which is used to forecast the possibility of a target variable. The dependent variable would have two classes, or we can say that it is binary coded as either 1 or 0, where 1 stands for the Yes and 0 standsContinue Reading
What is the Classification Algorithm? The Classification algorithm is a Supervised Learning technique that is used to identify the category of new observations on the basis of training data. In Classification, a program learns from the given dataset or observations and then classifies new observation into a number of classesContinue Reading
Introduction to Linear Regression Linear regression is the most important statistical algorithm in machine learning to learn the correlation between a dependent variable and one or more independent features. So, we can say that the linear relation between two variables can be stated as the change (increase/decrease) in the valueContinue Reading
What is Unsupervised Learning? As the name suggests, unsupervised learning is a machine learning technique in which models are not supervised using training dataset. Instead, models itself find the hidden patterns and insights from the given data. It can be compared to learning which takes place in the human brainContinue Reading
What is Supervised Machine Learning? Supervised machine learning is a learning model in which we train the machine by input and what is the desired output. Basically, we will train the model with a set of input variables(x) and the corresponding output variables(y) and try to create a relation betweenContinue Reading
Before starting a machine learning project, data is an essential thing needed before starting a project. The data used in ML projects is in CSV (Comma Separated Value) format. It is the most common as well as simple format formats of data used in ML projects, as it is usedContinue Reading
A machine learns from a trained data set to create a model. Whenever there is a new input to the algorithm, it predicts on the basis of the model. The evaluation is made in terms of accuracy, and the algorithm is deployed only if the accuracy is accepted by theContinue Reading
You cannot copy content of this page
WhatsApp us