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Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
30+ files (v0.9) CSV Anomaly detection: 2020 (continually updated) [330] [331] Iurii D. Katser and Vyacheslav O. Kozitsin On the Evaluation of Unsupervised Outlier Detection: Measures, Datasets, and an Empirical Study Most data files are adapted from UCI Machine Learning Repository data, some are collected from the literature.
.dat – not specific file type, often generic extension for "data" files for a variety of applications, sometimes used for general data contained within the .PK3/PK4 files .fontdat – a .dat file used for formatting game fonts.roq – Video format.sav – Savegame/Savefile format
Forms Data Format is defined in the PDF specification (since PDF 1.2). The Forms Data Format can be used when submitting form data to a server, receiving the response, and incorporating it into the interactive form. It can also be used to export form data to stand-alone files that can be imported back into the corresponding PDF interactive form.
This file is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.: You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work
A delimited text file is a text file used to store data, in which each line represents a single book, company, or other thing, and each line has fields separated by the delimiter. [3] Compared to the kind of flat file that uses spaces to force every field to the same width, a delimited file has the advantage of allowing field values of any length.
Symbolic Link (SYLK) is a Microsoft file format typically used to exchange data between applications, specifically spreadsheets. SYLK files conventionally have a .slk suffix. Composed of only displayable ANSI characters, it can be easily created and processed by other applications, such as databases .
We propose a deep learning approach that utilizes both word level and sentence-level representations to extract the relationships between treatment and problem. While deep learning techniques demand a large amount of data for training, we make use of a rule-based system particularly for relationship classes with fewer samples.