Classification & Prediction in Data Mining

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Classification and prediction basics

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20524UBCA037 T. PRASANTHI

India

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Classification & Prediction in Data Mining

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Froggy Jumps Classification & Prediction in Data MiningVersión en línea Classification and prediction basics por 20524UBCA037 T. PRASANTHI 1 What is the primary goal of classification in data mining? a Assign instances to predefined classes b Discover new data patterns without labels c Estimate numerical values 2 What distinguishes prediction from classification? a Prediction estimates continuous values; classification assigns categories b Prediction uses unlabeled data; classification uses labeled data c Prediction evaluates models; classification creates data 3 Which method is commonly used for classification with probabilistic outputs? a Principal Component Analysis b Naive Bayes c K-means clustering 4 What type of data split is essential to evaluate model performance fairly? a Full-data fit b Train-test split c Leave-one-out only on validation set 5 Which metric measures the proportion of correct predictions in classification? a Mean Squared Error b Accuracy c AUC-ROC 6 Which tool helps handle overfitting by validating on unseen data? a Cross-validation b Data normalization c Feature scaling 7 What is a confusion matrix used for in classification? a To measure data distribution b To visualize clustering structure c To summarize true/false positives and negatives 8 Which algorithm creates a tree-like model of decisions? a Decision Tree b Linear Regression c K-Means 9 In predictive modeling, what is regression primarily used for? a Classifying into discrete categories b Predicting continuous numeric values c Clustering similar records 10 Which concept helps prevent overfitting by simplifying models? a Data encryption b Regularization c Feature extraction

Froggy Jumps

Classification & Prediction in Data MiningVersión en línea

Classification and prediction basics

por 20524UBCA037 T. PRASANTHI

What is the primary goal of classification in data mining?

Assign instances to predefined classes

Discover new data patterns without labels

Estimate numerical values

What distinguishes prediction from classification?

Prediction estimates continuous values; classification assigns categories

Prediction uses unlabeled data; classification uses labeled data

Prediction evaluates models; classification creates data

Which method is commonly used for classification with probabilistic outputs?

Principal Component Analysis

Naive Bayes

K-means clustering

What type of data split is essential to evaluate model performance fairly?

Full-data fit

Train-test split

Leave-one-out only on validation set

Which metric measures the proportion of correct predictions in classification?

Mean Squared Error

Accuracy

AUC-ROC

Which tool helps handle overfitting by validating on unseen data?

Cross-validation

Data normalization

Feature scaling

What is a confusion matrix used for in classification?

To measure data distribution

To visualize clustering structure

To summarize true/false positives and negatives

Which algorithm creates a tree-like model of decisions?

Decision Tree

Linear Regression

K-Means

In predictive modeling, what is regression primarily used for?

Classifying into discrete categories

Predicting continuous numeric values

Clustering similar records

Which concept helps prevent overfitting by simplifying models?

Data encryption

Regularization

Feature extraction

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Classification & Prediction in Data Mining

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Classification & Prediction in Data MiningVersión en línea

por 20524UBCA037 T. PRASANTHI

What is the primary goal of classification in data mining?

What distinguishes prediction from classification?

Which method is commonly used for classification with probabilistic outputs?

What type of data split is essential to evaluate model performance fairly?

Which metric measures the proportion of correct predictions in classification?

Which tool helps handle overfitting by validating on unseen data?

What is a confusion matrix used for in classification?

Which algorithm creates a tree-like model of decisions?

In predictive modeling, what is regression primarily used for?

Which concept helps prevent overfitting by simplifying models?

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