×
Instructions
Select the testing data to predict its class, and then click the
ADD
button.
Now, click on the
NEXT
button to initiate the training phase for the Naive Bayes model.
Enter the occurrences of Yes(h) and No(-h) from the DATASET to calculate
Prior Probabilities
, then click
SUBMIT
.
Click on the
NEXT
button to calculate
Likelihood Probabilities
for every word in the testing data.
Input the number of times the word occurs in documents labeled with the specific class(Yes), and then click the
SUBMIT
button.
Now, follow the same procedure for class No. Now, click on
NEXT
to proceed further.
Note:
If a zero probability is encountered, then apply Laplace smoothing.
Calculate the
Posterior Probability
by entering the required values for P(h|d₇) and click on the
SUBMIT
button.
Click on the 'Prior Probability' tab given on the left side of the page to view the required values.
Next, click on the 'Likelihood Probability' tab and and observe the necessary values.
Repeat the previous step(7) to calculate the
Posterior Probability
for P(-h|d₇).
After submitting the values, click on the
NEXT
button to access the final result.
DATASET
TRAINING
PREDICTION
INSTRUCTIONS
TESTING SET
SELECT
:
NULL
Love Pain Joy Love Kick
Good Love Kick Joy
Pain Kick Joy Love
ADD
RESET
NEXT
DATASET
Document ID
Keywords in the document
Class h
1
Love Happy Joy Joy Happy
Yes
2
Happy Love Kick Joy Happy
Yes
3
Love Move Joy Good
Yes
4
Love Happy Joy Love Pain
Yes
5
Joy Love Pain Kick Pain
No
6
Pain Pain Love Kick
No
ARCHITECTURE