Cohort Classification Task - Revision history

Kyranstar at 21:03, 12 April 2018

2018-04-12T21:03:45Z

Kyranstar at 20:52, 12 April 2018

2018-04-12T20:52:19Z

Kyranstar at 20:38, 12 April 2018

2018-04-12T20:38:04Z

Kyranstar at 20:30, 12 April 2018

2018-04-12T20:30:36Z

Kyranstar at 20:26, 12 April 2018

2018-04-12T20:26:22Z

Kyranstar: Created page with "Excel sheet location: E:\McNair\Projects\Accelerators\Spring 2018\demo_day_classifier\DemoDayHTMLFull\demo_day_cohort_lists.xlsx The task is basically to classify whether o..."

2018-04-12T20:19:20Z

Created page with "Excel sheet location: E:\McNair\Projects\Accelerators\Spring 2018\demo_day_classifier\DemoDayHTMLFull\demo_day_cohort_lists.xlsx The task is basically to classify whether o..."

New page

Excel sheet location:
E:\McNair\Projects\Accelerators\Spring 2018\demo_day_classifier\DemoDayHTMLFull\demo_day_cohort_lists.xlsx

The task is basically to classify whether or not the HTML files contain cohort lists. There are many nuances in classifying this, because we want a balanced and correct dataset. If you are ever unsure how to classify something, just leave it blank.

Steps:
1. Click on the link to the HTML file under the column "Link" (Not the URL, as HTML files can be different than the URL)
2. If the file contains a list of cohort companies, mark it as a 1 under the column "cohort." If not, mark it a 0. These pages do not necessarily have to be about the accelerator that the row is about, it could just be any list of cohort companies for any demoday.

It would probably be better not to do this sequentially, because having a balanced dataset of many types of pages is useful. Also, if you see a certain page that shows up many times (For example, the "Pardon the Interruption" page), you don't need to classify it multiple times. Just leave the rest blank.

Also, it is better to have a balanced set of 1's and 0's. It's not really useful to have a huge list of 0's, when there are only a few 1's (as the classifier only takes as many 0's as there are 1's to have a 50/50 set). So it's probably better to look for pages that are likely to list cohort companies and look at those first.

If you want examples of pages with and without cohort lists, you can look at some of the already classified examples.

← Older revision		Revision as of 21:03, 12 April 2018
Line 12:		Line 12:
	Also, it is better to have a balanced set of 1's and 0's. It's not really useful to have a huge list of 0's, when there are only a few 1's (as the classifier only takes as many 0's as there are 1's to have a 50/50 set). So it's probably better to look for pages that are likely to list cohort companies and look at those first.		Also, it is better to have a balanced set of 1's and 0's. It's not really useful to have a huge list of 0's, when there are only a few 1's (as the classifier only takes as many 0's as there are 1's to have a 50/50 set). So it's probably better to look for pages that are likely to list cohort companies and look at those first.

−	If you want examples of pages with and without cohort lists, you can look at some of the already classified examples.	+	If you want examples of pages with and without cohort lists, you can look at some of the already classified examples, though there might be a few mistakes.

@@ Line 8: / Line 8: @@
 . If the file contains a list of cohort companies, mark it as a 1 under the column "cohort." If not, mark it a 0. These pages do not necessarily have to be about the accelerator that the row is about, it could just be any list of cohort companies for any demoday. Even if the webpage links to a list of cohorts, still mark it 0. It must contain a list of cohorts to be marked 1.
-It would probably be better not to do this sequentially, because having a balanced dataset of many types of pages is useful. Also, if you see a certain page that shows up many times (For example, the "Pardon Our Interruption" page), you don't need to classify it multiple times. Just leave the rest blank.
+It would probably be better not to do this sequentially, because having a balanced dataset of many types of pages is useful. Also, if you see a certain page that shows up many times (For example, the "Pardon Our Interruption" page), you don't need to classify it multiple times. Just leave the rest blank. Also, ignore eventbrite pages, because the HTML sometimes has cohort lists even though it's not visible in the browser.
 Also, it is better to have a balanced set of 1's and 0's. It's not really useful to have a huge list of 0's, when there are only a few 1's (as the classifier only takes as many 0's as there are 1's to have a 50/50 set). So it's probably better to look for pages that are likely to list cohort companies and look at those first.
 If you want examples of pages with and without cohort lists, you can look at some of the already classified examples.

@@ Line 6: / Line 6: @@
 Steps:
 . Click on the link to the HTML file under the column "Link" (Not the URL, as HTML files can be different than the URL)
-. If the file contains a list of cohort companies, mark it as a 1 under the column "cohort." If not, mark it a 0. These pages do not necessarily have to be about the accelerator that the row is about, it could just be any list of cohort companies for any demoday.
+. If the file contains a list of cohort companies, mark it as a 1 under the column "cohort." If not, mark it a 0. These pages do not necessarily have to be about the accelerator that the row is about, it could just be any list of cohort companies for any demoday. Even if the webpage links to a list of cohorts, still mark it 0. It must contain a list of cohorts to be marked 1.
 It would probably be better not to do this sequentially, because having a balanced dataset of many types of pages is useful. Also, if you see a certain page that shows up many times (For example, the "Pardon Our Interruption" page), you don't need to classify it multiple times. Just leave the rest blank.

@@ Line 2: / Line 2: @@
    E:\McNair\Projects\Accelerators\Spring 2018\demo_day_classifier\DemoDayHTMLFull\demo_day_cohort_lists.xlsx
-The task is basically to classify whether or not the HTML files contain cohort lists. There are many nuances in classifying this, because we want a balanced and correct dataset. If you are ever unsure how to classify something, just leave it blank.
+The task is basically to classify whether or not the HTML files contain cohort lists. There are many nuances in classifying this, because we want a balanced and correct dataset. If you are ever unsure how to classify something, just leave it blank. Also, if the HTML page looks like it is missing important text that should be there, just skip it.
 Steps: