2022-05-11

May 11 In-Class Exercise.

Please post your solutions to the May 11 In-Class Exercise to this thread.
Best,
Chris
Please post your solutions to the May 11 In-Class Exercise to this thread. Best, Chris
2022-05-12

-- May 11 In-Class Exercise
P@100 = x N = 5000 = corpus K = 100 = batch N/X = # batches = 5000/100 = 50 batches N-X = threshold = 5600 - 100 = 4900 K=pN > 100 = p*5000 >p = row = 0.02
procedure would follow as: compute threshold (4900), go through all 50 batches, get document that scores over 4900, determine the relevance ( human test), then calculate precision and the average of all the batches, Compute aggregate P@100.
P@100 = x N = 5000 = corpus K = 100 = batch N/X = # batches = 5000/100 = 50 batches N-X = threshold = 5600 - 100 = 4900 K=pN > 100 = p*5000 >p = row = 0.02 procedure would follow as: compute threshold (4900), go through all 50 batches, get document that scores over 4900, determine the relevance ( human test), then calculate precision and the average of all the batches, Compute aggregate P@100.

-- May 11 In-Class Exercise
N=5000 X = 100 documents N / X = 5000/ 100 = 50 batches N - X = 5000 - 100 = 4900
Check for every doc if the score is greater than 900 and if the doc is relevant. Then the list is made: successful_docs The precision for a batch = length / succesful_docs
P@100 = Average of the precision for each batch.
N=5000 X = 100 documents N / X = 5000/ 100 = 50 batches N - X = 5000 - 100 = 4900 Check for every doc if the score is greater than 900 and if the doc is relevant. Then the list is made: successful_docs The precision for a batch = length / succesful_docs P@100 = Average of the precision for each batch.

-- May 11 In-Class Exercise
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2022-05-13

-- May 11 In-Class Exercise
N=5000 X = 100 documents 
N / X = 5000/ 100 = 50 batches
N - X = 5000 - 100 = 4900
go through all 50 batches
get document that scores over 4900
determine the relevance 
Compute precision 
Compute the average of all the batches
Calculate aggregate P@100 
<pre>N=5000 X = 100 documents N / X = 5000/ 100 = 50 batches N - X = 5000 - 100 = 4900 go through all 50 batches get document that scores over 4900 determine the relevance Compute precision Compute the average of all the batches Calculate aggregate P@100 </pre>
2022-05-14

-- May 11 In-Class Exercise
N=5000 documents
Batch size is 100
X documents score > N−X documents 
 
Number of batches= 5000/100= 50 
 
To compute aggregate P@k,
1) Scan all the batches to find relevant documents that score over the threshold.
2) Check whether the document is relevant to query.
3) Calculate precision
4) Calculate average precision  
5) Caluclaute aggregate precision P@100 where
if 100 documents score over threshold here N_X. ρ =k/N= 100/5000= 0.02 where X= 100 
 
<pre> N=5000 documents Batch size is 100 X documents score > N−X documents Number of batches= 5000/100= 50 To compute aggregate P@k, 1) Scan all the batches to find relevant documents that score over the threshold. 2) Check whether the document is relevant to query. 3) Calculate precision 4) Calculate average precision 5) Caluclaute aggregate precision P@100 where if 100 documents score over threshold here N_X. ρ =k/N= 100/5000= 0.02 where X= 100 </pre>

-- May 11 In-Class Exercise
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-- May 11 In-Class Exercise
N=5000 X = 100 documents, N / X = 5000/ 100 = 50, N - X = 5000 - 100 = 4900 check whichever documents score is greater than 4900 check the relevancy of the document calculate precision find out the average of all the documents Calculate aggregate P@100
(Edited: 2022-05-14)
N=5000 X = 100 documents, N / X = 5000/ 100 = 50, N - X = 5000 - 100 = 4900 check whichever documents score is greater than 4900 check the relevancy of the document calculate precision find out the average of all the documents Calculate aggregate P@100

-- May 11 In-Class Exercise
Resource Description for Screen Shot 2022-05-15 at 10.43.28 AM.png
((resource:Screen Shot 2022-05-15 at 10.43.28 AM.png|Resource Description for Screen Shot 2022-05-15 at 10.43.28 AM.png))

-- May 11 In-Class Exercise
Given, N = 5000 X = 100 Number of batches = N/X = 50 Threshold score = N - X = 4900
For every batch, 1. Find documents above the score of 4900 and determine if it is relevant or not 2. Calculate precision 3. Calculate the average precision of all batches
Calculate aggregate P@100
Given, N = 5000 X = 100 Number of batches = N/X = 50 Threshold score = N - X = 4900 For every batch, 1. Find documents above the score of 4900 and determine if it is relevant or not 2. Calculate precision 3. Calculate the average precision of all batches Calculate aggregate P@100
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