Classification
Random Forest
Random Forest Description Random Forest is a Supervised Machine Learning algorithm. It works on the Bagging (Bootstrap Aggregation) principle of the Ensemble technique. Thus, it uses multiple models instead of a single model to make predictions. It ...
Gradient Boosting in Classification
Gradient Boosting in Classification Description Gradient boosting is a machine learning algorithm. It is a learning method that combines multiple predictive models like decision tree to create a strong predictive model. Why use High Predictive ...
Extreme Gradient Boost Classification
Extreme Gradient Boost Classification Description Extreme Gradient Boost (XGBoost) is a Decision Tree-based ensemble algorithm. XGBoost uses a gradient boosting framework. It approaches the process of sequential tree building using parallelized ...
Decision Tree
Decision Tree Description Decision Tree builds a classification model in the form of a tree structure where each leaf node represented a class or a decision. Why to use Data Classification When to use When the data is categorized into Boolean values. ...
Categorical Naive Bayes
Categorical Naive Bayes Description The categorical Naïve Bayes algorithm is suitable for categorically discrete values like Weather Prediction, and Medical Diagnosis. It is the simplest and fastest classification algorithm. Why to use It is the ...
Binomial Logistic Regression
Binomial Logistic Regression Description Binomial Logistic Regression predicts the probability that an observation falls into one of the two categories of the binary dependent variable, based on one or more, categorical or continuous independent ...
AdaBoost in Classification
AdaBoost in Classification Description AdaBoost is a technique in Machine Learning used as an Ensemble Method. AdaBoost is a boosting algorithm that combines the predictions of multiple weak classifiers to create a strong classifier. Why to use ...
Classification
Classification is the process of predicting the class of given data points. Classes are referred to as targets/ labels or categories. Classification predictive modeling is the task of approximating a mapping function (f) from input variables (X) to ...
Popular Articles
Sequence Generator
Sequence Generator Description Sequence Generator adds a sequence column to your dataset. Why to use To add Surrogate Keys, Primary Keys to the dataset. When to use When you want to add a sequence column to your dataset. When not to use — ...
Keyboard Shortcuts in Dashboard
Keyboard shortcuts are helpful for enhancing user efficiency. Rubiscape provides you with various shortcut keys to move around the RubiSight dashboard and perform tasks using keyboards. The table below describes the shortcuts available in rubiscape ...
Using Filters
When you plot a chart, all the data in the dataset is not required to be used. Also, within the data used, there might be sub-categories that you want to plot separately. You can view classified results in the charts using filters. Filters help you ...
Changing the Workspace
A workspace is a place where you can manage multiple datasets and projects. Workspaces are the parent structures that include datasets and projects. Workspaces are mapped to the login, which means you may have limited access to specific workspaces as ...
Advcance Course in AI_ML-Application form filling Guide
Course Application Help Guide Please follow the process below mentioned, for course application. 1. Register yourself on [ https://campus.unipune.ac.in/ccep/login.aspx ] 2. Select your Nationality and fill in Email id 3. Verify your email address 4. ...