We are providing the machine learning assignment help in all machine learning algorithms, translations, audio, NLP and video reorganization.
In the last of this blog we will add one example using python machine learning algorithm and method to fit it into the model of the machine learning.
Machine Learning Algorithm
Supervised Learning
Unsupervised Learning
Supervised Learning
Decision Trees: It is a decision tree support tool that uses a tree-like graph or model of decisions and possible events of sub-sequences.
Naive Bayes Classification: It family of simple probabilistic classifiers based on applying Bayes’ theorem
Ordinary Least Squares Regression: Least squares is a method for performing linear regression
Logistic Regression: Logistic regression is a powerful statistical way of modeling a binomial outcome with one or more explanatory variables
Support Vector Machines: It is a binary classification algorithm which is used in given a set of points of 2 types in N dimensional place, SVM generates a (N — 1) dimensional hyperplane to separate those points into 2 groups.
Unsupervised Learning
Clustering Algorithms: In this the data points is given into the set of group(cluster) and the find the centro-id of these cluster algorithms like k-mean cluster etc.
Principal Component Analysis: It is used in uses an orthogonal transformation.
How to fit these algorithm into the model
Step1:
First clean the data, by using removing punctuation, spaces and newlines etc.
Step2:
After this change data into the integer format if data is given in string format.
Step3:
After this fit it into the models.
And after this split the data and then predict the result.
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