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Topic: "extra-tree-classifiers"

prakhargurawa/Titanic-Survival-Predictor

Trying to predict survival rate of passengers using algorithms like Logistic Regression, Ada Boost, Gradient Boost , Decision Tree Classifiers , Extra Tree Classifiers , Random Forest Classifiers and XG Boost with appropriate data preprocessing techniques.

Language: Jupyter Notebook - Size: 53.7 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

vasupatelll/Email_Spam_Classifier

A Machine Learning Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like MultinomialNB, LogisticRegression, SVC, DecisionTreeClassifier, RandomForestClassifier, KNeighborsClassifier, AdaBoostClassifier, BaggingClassifier, ExtraTreesClassifier, GradientBoostingClassifier, XGBClassifier to compare accuracy an

Language: Jupyter Notebook - Size: 660 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

anandanraju/Eligibility_Validation_Report_Model_for_Borrowing_Money_From_Bank

In simple, a Loan (borrowing money from a bank) is the sum of money that you borrow from the bank or lending financial institution in order to meet needs. These needs could result from planned or unplanned events, and by borrowing, you incur a debt that you have to pay within the agreed duration on your contract.

Language: Jupyter Notebook - Size: 11.8 MB - Last synced at: 10 days ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

anandanraju/Titanic_Survival_Prediction_Model

The sinking of the RMS Titanic is one of the most infamous shipwrecks in world history. In this model, need to analyse what sorts of people were likely to survive. We also need to apply the tools of machine learning to predict which passengers survived in this tragedy.

Language: Jupyter Notebook - Size: 544 KB - Last synced at: 10 days ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

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