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Last updated Aug 11, 2023 Edit Source

Created: 2022-11-02 20:11:09 Tags: #ML #DataScience #classification_metric #ml_metrics

For understanding precision score you need to read Confusion Matrix

Confusion Matrix

Created: 2022-11-01 15:11:91 Tags: #ML #DataScience #confusionmatrix #classificationmetric Note In the field of , confusion matrix also know as an...

11/13/2023

note firstly.

# Note

Precision uses to evaluate classification machine learning algorithm. It has more stability with imbalanced data then Accuracy score

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# Definition

Precision is the fraction of relevant instances among the retrieved instances. In other words how many retrieved samples are relevant?. $Precision = \frac{TP}{TP + FP}$

# Probabilistic interpretation

Precision is the estimated probability that a document randomly selected from the pool of retrieved documents are relevant.

Relevant element (document) is the element (document) has a positive class label.

# Advantages

Good works with imbalanced data
Easy interpretable

Recall

Recall

Created: 2022-11-02 20:11:09 Tags: #ML #DataScience #classificationmetric #mlmetrics [!WARNING] For understanding recall score you need to read Confusion Matri note firstly. Note Recall uses to...

11/13/2023
F measure

F measure

Created: 2022-11-02 22:11:63 Tags: #ML #DataScience #classificationmetric #mlmetrics [!WARNING] For understanding this metrics, you need to know what is Precisio and Recal firstly Note F...

11/13/2023
Accuracy score

Accuracy score

Created: 2022-11-01 13:11:07 Tags: #ML #DataScience #classificationmetric #mlmetrics Note Accuracy is one of the metrics for classification model evaluation. Informally, accuracy is a fraction...

11/13/2023
Balanced accuracy score

# References

Precision and recall from Wikipedia

# Zero Links

Classification Metrics

Classification Metrics

Created: 2022-11-01 14:11:47 Tags: #ML #DataScience #classificationmetric #mlmetrics Note When you built classification mode you need to measure it performance. For a...

11/13/2023

Backlinks

Accuracy score

Accuracy score

...Easy for calculation Disadvantages Works badly with imbalabced class problem. For imbalanced classes you can use Precisio, Recal and F measur to evaluate model performance. Related metrics Precisio Recal F measur References Sklearn accuracy score Zero Links Classification......

11/13/2023
Classification Metrics

Classification Metrics

...part of classification problems you can use these metrics for model evaluation: To calculate some metrics you need to know what is Confusion Matri Accuracy scor Precisio Recal F measur ROC Curve & ROC AU Zero Links ML......

11/13/2023
Confusion Matrix

Confusion Matrix

...as: $TPR=\frac{TP}{TP + FN}$ Also known as fall-out ration defines as: $FPR = \frac{FP}{FP + TN}$ [!INFO] We can use TRP and FPR to define ROC Curve & ROC AU References Confusion matrix explanation TRP FPR Zero Links Classification......

11/13/2023
F measure

F measure

...between Precisio and Recal; - Use $F_2$ ( $\beta=2$ ) if Recal value is more important than Precisio (weights recall higher than precision); - Use $F_{0.5}$ ( $\beta=0.5$ ) if Precisio value is more important than Recal (weights precision higher than recall). Related metrics......

11/13/2023
ROC Curve & ROC AUC

ROC Curve & ROC AUC

...AUC is related to the by the formula: $G_1 = 2AUC - 1$ where: $G1 = 1 - \displaystyle\sum{k=1}^{n} (Xk - X{k-1})(Yk - Y_{k-1})$ Related metrics Precisio Recal F measur Accuracy scor References ROC curve Wikipedia Zero Links Classification......

11/13/2023
Recall

Recall

...element (document) is the element (document) has a positive class label. Advantages Good works with imbalanced data Easy interpretable Related metrics Precisio F measur Accuracy scor References Precision and recall from Wikipedia Zero Links Classification Metric
11/13/2023

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