Wiki Article · Cinematic

F1 Score

F1 score machine learning me ek evaluation metric hai jo precision aur recall ka harmonic mean hai.…

Overview

F1 Score — Quick Facts

📌

Property: Detail

🎯

Full Name: F1 Score (F-measure, F1-measure)

⚡

Category: Machine Learning, Model…

🔑

Formula: $F1 = 2 \times \frac{Precision…

Topic 1

Prerequisites: Confusion Matrix

💡

TP (True Positive): Model ne…

🔑

FP (False Positive): Model ne…

⚡

FN (False Negative): Model ne…

🎯

TN (True Negative): Model ne…

Topic 2

Precision aur Recall

💡

"Jab model positive bolta hai, to…

🔑

High precision = kam false alarms

⚡

Example: Spam filter — precision…

🎯

"Actual positives me se kitne…

Topic 3

F1 Score Formula

💡

TP = 80, FP = 20, FN = 10

🔑

Precision = 80 / (80 + 20) = 0.80

⚡

Recall = 80 / (80 + 10) = 0.89

🎯

F1 = 2 × (0.80 × 0.89) / (0.80 +…

Topic 4

Kyun Harmonic Mean

⭐ Arithmetic mean (simple average) use kyun nahi? | Scenario | Precision | Recall |…

Topic 5

F1 vs Accuracy

💡

Accuracy = 990/1000 = 99% (looks…

🔑

Precision = 0/0 = undefined (no…

⚡

Recall = 0/10 = 0% (missed all…

🎯

F1 = 0 (correctly shows model is…

Topic 6

F-Beta Score

💡

$\beta < 1$: Precision important —…

🔑

$\beta = 1$: Equal weight —…

⚡

$\beta > 1$: Recall important —…

Topic 7

Multi-Class F1

💡

Macro = treats all classes equally…

🔑

Micro = treats all samples equally…

⚡

Weighted = class size ke hisaab se…

Topic 8

Practical Examples

💡

False Negative (miss) bahut costly…

🔑

Recall zyada important → F2 score…

⚡

F1 minimum threshold: 0.85+…

🎯

False Positive costly → important…

Topic 9

F1 Decision Flow

📚 `mermaid flowchart TD A[Classification Model Evaluation] --> B{Classes Balanced?} B…

Topic 10

Limitations

💡

Binary bias — originally binary…

🔑

True Negatives ignore — F1 TN…

⚡

Threshold dependent —…

🎯

Single number — F1 ek number hai —…

Topic 11

Best Practices

🎯 1. Imbalanced data me F1 > Accuracy — hamesha F1 dekho jab classes imbalanced hon 2.…

Comparison

F1 vs Accuracy

⚖️

Formula: (TP + TN) / Total

⚖️

Considers TN?: Haan

⚖️

Imbalanced data?: Misleading

Diagram

Visual Flow

📊 Diagram visualization — details in narration

Quiz — Question 1

F1 Score ka sabse sahi definition kya hai?

Quick Quiz

Quiz — Question 2

F1 Score ka 'Full Name' kya hai?

Complete! 🎉

F1 Score Complete!

Aliens Wiki · HIEN · Cinematic Knowledge

✅

F1 Score Complete

➡️

F1 Score

F1 Score — Quick Facts

Property: Detail

Full Name: F1 Score (F-measure, F1-measure)

Category: Machine Learning, Model…

Formula: $F1 = 2 \times \frac{Precision…

Prerequisites: Confusion Matrix

TP (True Positive): Model ne…

FP (False Positive): Model ne…

FN (False Negative): Model ne…

TN (True Negative): Model ne…

Precision aur Recall

"Jab model positive bolta hai, to…

High precision = kam false alarms

Example: Spam filter — precision…

"Actual positives me se kitne…

F1 Score Formula

TP = 80, FP = 20, FN = 10

Precision = 80 / (80 + 20) = 0.80

Recall = 80 / (80 + 10) = 0.89

F1 = 2 × (0.80 × 0.89) / (0.80 +…

Kyun Harmonic Mean

F1 vs Accuracy

Accuracy = 990/1000 = 99% (looks…

Precision = 0/0 = undefined (no…

Recall = 0/10 = 0% (missed all…

F1 = 0 (correctly shows model is…

F-Beta Score

$\beta < 1$: Precision important —…

$\beta = 1$: Equal weight —…

$\beta > 1$: Recall important —…

Multi-Class F1

Macro = treats all classes equally…

Micro = treats all samples equally…

Weighted = class size ke hisaab se…

Practical Examples

False Negative (miss) bahut costly…

Recall zyada important → F2 score…

F1 minimum threshold: 0.85+…

False Positive costly → important…

F1 Decision Flow

Limitations

Binary bias — originally binary…

True Negatives ignore — F1 TN…

Threshold dependent —…

Single number — F1 ek number hai —…

Best Practices

F1 vs Accuracy

Formula: (TP + TN) / Total

Considers TN?: Haan

Imbalanced data?: Misleading

Visual Flow

See Also

Precision

Recall

Confusion Matrix

Accuracy

Classification

Machine Learning

Quiz — Question 1

Quiz — Question 2

F1 Score Complete!

F1 Score Complete

Precision