See Click Predict Fix from Kaggle competition number of views prediction

eCommerce problem from Tatvic blog

Train file: 2133 rows

Source

Dataset at Tatvic blog post

Kaggle Higgs Boson Machine Learning Challenge

Source

Kaggle Challenge

American Colleges and Universities

Source

mathforum.org datasets

Playmate of the Year stats 1957-2012. Bust prediction.

Credits: Based in the Nathany dataset (1960-2007)

http://buzzdata.com/nathany/playboy-bust

Library visits patterns based on 8000+ public Libraries in USA.

Source

National Center for Education Statistics

Description

The objective is to identify each of a large number of black-and-white rectangular pixel displays as one of the 26 capital letters in the English alphabet. The character images were based on 20 different fonts and each letter within these 20 fonts was randomly distorted to produce a file of 20,000 unique stimuli. Each stimulus was converted into 16 primitive numerical attributes (statistical moments and edge counts) which were then scaled to fit into a range of integer values from 0 through 15. We typically train on the first 16000 items and then use the resulting model to predict the letter category for the remaining 4000. See the article cited above for more details.

Attribute Information:
letter - capital letter (26 values from A to Z)
x-box - horizontal position of box (integer)
y-box - vertical position of box (integer)
width - width of box (integer)
high - height of box (integer)
onpix - total # on pixels (integer)
x-bar - mean x of on pixels in box (integer)
y-bar - mean y of on pixels in box (integer)
x2bar - mean x variance (integer)
y2bar - mean y variance (integer)
xybar - mean x y correlation (integer)
x2ybr - mean of x * x * y (integer)
xy2br - mean of x * y * y (integer)
x-ege - mean edge count left to right (integer)
xegvy - correlation of x-ege with y (integer)
y-ege - mean edge count bottom to top (integer)
yegvx - correlation of y-ege with x (integer)

Source

Letter Image Recognition Data from Delve datasets and UCI

See Click Predict Fix from Kaggle competition votes prediction

See Click Predict Fix from Kaggle competition number of comments prediction