Examples of using Classification and regression in English and their translations into Indonesian
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Classification and regression methods.
We present results for both classification and regression problems.
Classification and regression algorithms are types of supervised learning algorithms.
Some examples of predictive modeling are classification and regression.
CART= Classification and regression tree.
There are two types of predictive models: classification and regression.
Supervised learning uses classification and regression techniques to develop these predictive models.
In this sense, we have two predictive models: classification and regression.
Classification and regression are types of supervised learning while, clustering is unsupervised learning.
Another is"CART"(Classification and Regression Trees).
The two main types of problemssolved by machine learning applications are classification and regression.
Surveillance using CART(classification and regression tree).
The Support Vector Machine(SVM)is one of the most popular machine learning algorithms for classification and regression.
As there are specific decision tree methods that include Classification and Regression Trees and Chi-Square Automatic Interaction Detection(CHAID).
The course introduces students to the theoretical foundations of machine learning and data science, as wellas to the solution of real business problems with the help of computer vision, classification and regression algorithms.
Another technique that is used for both classification and regression problems.
Classification and regression trees(CART) is a non-parametric technique that produces either classification or regression trees, depending on whether the dependent variable is categorical or numeric, respectively.
There are two main types of predictive models: classification and regression models.
The Support Vector Machine is a machine learning method for classification and regression and is fast replacing neural networks as the tool of choice for prediction and pattern recognition tasks, primarily due to their ability to generalise well on unseen data.
There are two types of predictive models which include classification and regression models.
Notable ones include: ID3(Iterative Dichotomiser 3) C4.5(successor of ID3)CART(Classification And Regression Tree) CHAID CHi-squared Automatic Interaction Detector.
Mainly, it focuses on kernel machines like support vector machines for classification and regression problem.
The data mining approach used was CART(Classification and Regression Trees).
The two methods include logistic regression and classification and regression tree(CART).
Bagging leads to"improvements for unstable procedures"(Breiman, 1996), which include, for example,artificial neural networks, classification and regression trees, and subset selection in linear regression Breiman, 1994.
They are learningmachines that are used to perform binary classifications and regression estimates.