Update parquet files

README.md

@@ -1,92 +0,0 @@
----
-task_categories:
-- tabular-regression
-- tabular-classification
-tags:
-- tabular
-size_categories:
-- 10K<n<100K
----
-
-## Source
-Source: [UCI](https://archive.ics.uci.edu/ml/datasets/BlogFeedback)
-
-## Data Set Information:
-
-This data originates from blog posts. The raw HTML-documents
-of the blog posts were crawled and processed.
-The prediction task associated with the data is the prediction
-of the number of comments in the upcoming 24 hours. In order
-to simulate this situation, we choose a basetime (in the past)
-and select the blog posts that were published at most
-72 hours before the selected base date/time. Then, we calculate
-all the features of the selected blog posts from the information
-that was available at the basetime, therefore each instance
-corresponds to a blog post. The target is the number of
-comments that the blog post received in the next 24 hours
-relative to the basetime.
-
-In the train data, the basetimes were in the years
-2010 and 2011. In the test data the basetimes were
-in February and March 2012. This simulates the real-world
-situtation in which training data from the past is available
-to predict events in the future.
-
-The train data was generated from different basetimes that may
-temporally overlap. Therefore, if you simply split the train
-into disjoint partitions, the underlying time intervals may
-overlap. Therefore, the you should use the provided, temporally
-disjoint train and test splits in order to ensure that the
-evaluation is fair.
-
-## Attribute Information:
-
-1...50:Average, standard deviation, min, max and median of them attributes 51...60 for the source of the current blog post. With source we mean the blog on which the post appeared.
-For example, myblog.blog.org would be the source of the post myblog.blog.org/post_2010_09_10
-
-51: Total number of comments before basetime
-
-52: Number of comments in the last 24 hours before the
-basetime
-
-53: Let T1 denote the datetime 48 hours before basetime,
-Let T2 denote the datetime 24 hours before basetime.
-This attribute is the number of comments in the time period
-between T1 and T2
-
-54: Number of comments in the first 24 hours after the
-publication of the blog post, but before basetime
-
-55: The difference of Attribute 52 and Attribute 53
-
-56...60:
-The same features as the attributes 51...55, but
-features 56...60 refer to the number of links (trackbacks),
-while features 51...55 refer to the number of comments.
-
-61: The length of time between the publication of the blog post
-and basetime
-
-62: The length of the blog post
-
-63...262:
-The 200 bag of words features for 200 frequent words of the
-text of the blog post
-
-263...269: binary indicator features (0 or 1) for the weekday
-(Monday...Sunday) of the basetime
-
-270...276: binary indicator features (0 or 1) for the weekday
-(Monday...Sunday) of the date of publication of the blog
-post
-
-277: Number of parent pages: we consider a blog post P as a
-parent of blog post B, if B is a reply (trackback) to
-blog post P.
-
-278...280:
-Minimum, maximum, average number of comments that the
-parents received
-
-281: The target: the number of comments in the next 24 hours
-(relative to basetime)

train.csv → wwydmanski--blog-feedback/csv-test.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:76c8930b410797030612bc783aac11b29573027c16d464f7a8c2c29e17c5e8d4
-size 65096339
+oid sha256:a5ecfa0c004fb4302c635bdb5248a664f33b901dab06904f5b383085dcedf0c9
+size 1344159

wwydmanski--blog-feedback/csv-train.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:84a4ffba4d81e8c3608491f721eacac7a9958822e02174d979c395030ed187b4
+size 5667726