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Confusion Matrix | Error Type I and II | Accuracy, Recall, Precision, Sensitivity | Machine Learning 

Ankit Verma
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confusion matrix | type i & type ii error | accuracy | misclassification | recall | precision | sensitivity | specificity | true positive | tp | true negative | tn | false positive | fp | false negative | fn | type i error | type ii error | types of errors | performance metrices | confusion metrices | confusion matrix | confusion matrix in machine learning | confusion matrix | accuracy, error rate, precision, recall explained with solved example | machine learning fundamentals: the confusion matrix | confusion matrix solved example accuracy precision recall | confusion matrix in machine learning | machine learning tutorial | examples | numerical | performance metrics, accuracy, precision, recall | confusion matrix, accuracy, precision and recall | the confusion matrix in machine learning | what is a confusion matrix? | confusion matrix, recall & specificity in machine learning | artificial intelligence and machine learning | aiml | artificial intelligence and data science | aids | ggsipu | ipu | mdu | du | iit | nit | niit | in | machine learning | ml | fundamentals of machine learning | fml | foml | ankit verma machine learning | ankit verma ml | ankit verma fml | ankit verma foml | av | ankit verma
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28 окт 2024

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