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CLASSIFICATION ALGORITHMBell-shaped assumptions for higher predictions⛳️ More CLASSIFICATION ALGORITHM, explained: · Dummy Classifier · K Nearest Neighbor Classifier · Bernoulli Naive Bayes ▶ Gaussian Naive Bayes · Decision Tree Classifier · Logistic Regression ·...

A workflow and code walkthrough for constructing a Bayesian regression model in STANNote: Try my previous article for a practical discussion on why Bayesian modeling could also be the appropriate selection in your task.This...

DATA PREPROCESSINGSix ways of matchmaking categories and numbers10 min read·19 hours agoAh, categorical data — the colourful characters in our datasets that machines just can’t seem to grasp. That is where “red” becomes 1,...

DATA PREPROCESSINGOne (tiny) dataset, six imputation methods?Let’s discuss something that each data scientist, analyst, or curious number-cruncher has to take care of in the end: missing values. Now, I do know what you’re considering...

Unlocking Predictive Power Through Binary SimplicityLike several algorithm in machine learning, Bernoulli Naive Bayes has its strengths and limitations.Simplicity: Easy to implement and understand.Efficiency: Fast to coach and predict, works well with large feature...

The friendly neighbor approach to machine learninglabels, predictions, accuracies = list(y_test), , k_list = for k in k_list:knn_clf = KNeighborsClassifier(n_neighbors=k)knn_clf.fit(X_train, y_train)y_pred = knn_clf.predict(X_test)predictions.append(list(y_pred))accuracies.append(accuracy_score(y_test, y_pred).round(4)*100)df_predictions = pd.DataFrame({'Label': labels})for k, pred in zip(k_list, predictions):df_predictions = preddf_accuracies...

Learn critical knowledge for constructing AI apps, in plain englishRetrieval Augmented Generation, or RAG, is all the craze nowadays since it introduces some serious capabilities to large language models like OpenAI’s GPT-4 — and...