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AI Club
AI Club
Classification - Accuracy
How do you
measure how
good a model
is?
Number of
Countries
Visited
Number of
Years in
School
Height
(Feet)
Original
Label
Who am
I?
15 13 5.0 Adult
2 3 3.5 Child
7 4 4.0 Child
1 5 7.0 Adult
How do you
measure how
good a model is?
• Create a “Validation/test
Dataset” – a part of the
training data put aside to
use when testing.
Number of
Countries
Visited
Number of
Years in
School
Height
(Feet)
Original
Label
Who am
I?
15 13 5.0 Adult
2 3 3.5 Child
7 4 4.0 Child
1 5 7.0 Adult
Validation/Test Dataset
20% of the Dataset
Training Data
80% of the Dataset
Dataset
How do you
measure how
good a model is?
Validation/Test Dataset
• Create a “Validation/test
Dataset” – a part of the
training data put aside to
use when testing.
• Validation dataset has the
actual (correct answer)
• After the model is trained,
use it to predict the
answer and compare
prediction to the actual
answer in the validation
dataset
Number of
Countries
Visited
Number of
Years in
School
Height (Feet) Original
Label Who
am I?
15 13 5.0 Adult
2 3 3.5 Child
7 4 4.0 Child
1 5 7.0 Adult
Comparing the
trained AI
predictions to the
actual answers
Correct Answers - 3
Incorrect Answers - 1
Actual
Answers
AI Prediction
Answers
• In classification, answer is
precisely right or wrong.
Right if it matches label, wrong
otherwise
(no matter how many categories
there are)
Number of
Countries
Visited
Number of
Years in
School
Height
(Feet)
Original Label
Who am I?
What the model
predicted
15 13 5.0 Adult Adult
2 3 3.5 Child Child
7 4 4.0 Child Child
1 5 7.0 Adult Child
Calculating Accuracy
• Correct Answers*100/Total
answers
• Closer to 100% the better
• We will see more metrics in
later projects
3 Correct * 100/ 4 Total = 75%
Actual
Answers
AI Prediction
Answers
Number of
Countries
Visited
Number of
Years in
School
Height
(Feet)
Original Label
Who am I?
What the model
predicted
15 13 5.0 Adult Adult
2 3 3.5 Child Child
7 4 4.0 Child Child
1 5 7.0 Adult Child
THANK YOU
https://aiclub.world
info@pyxeda.ai

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Accuracy middleschool

  • 3. How do you measure how good a model is? Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? 15 13 5.0 Adult 2 3 3.5 Child 7 4 4.0 Child 1 5 7.0 Adult
  • 4. How do you measure how good a model is? • Create a “Validation/test Dataset” – a part of the training data put aside to use when testing. Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? 15 13 5.0 Adult 2 3 3.5 Child 7 4 4.0 Child 1 5 7.0 Adult Validation/Test Dataset 20% of the Dataset Training Data 80% of the Dataset Dataset
  • 5. How do you measure how good a model is? Validation/Test Dataset • Create a “Validation/test Dataset” – a part of the training data put aside to use when testing. • Validation dataset has the actual (correct answer) • After the model is trained, use it to predict the answer and compare prediction to the actual answer in the validation dataset Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? 15 13 5.0 Adult 2 3 3.5 Child 7 4 4.0 Child 1 5 7.0 Adult
  • 6. Comparing the trained AI predictions to the actual answers Correct Answers - 3 Incorrect Answers - 1 Actual Answers AI Prediction Answers • In classification, answer is precisely right or wrong. Right if it matches label, wrong otherwise (no matter how many categories there are) Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? What the model predicted 15 13 5.0 Adult Adult 2 3 3.5 Child Child 7 4 4.0 Child Child 1 5 7.0 Adult Child
  • 7. Calculating Accuracy • Correct Answers*100/Total answers • Closer to 100% the better • We will see more metrics in later projects 3 Correct * 100/ 4 Total = 75% Actual Answers AI Prediction Answers Number of Countries Visited Number of Years in School Height (Feet) Original Label Who am I? What the model predicted 15 13 5.0 Adult Adult 2 3 3.5 Child Child 7 4 4.0 Child Child 1 5 7.0 Adult Child