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128-d PCA'd VGG-ish features every 1 second. 2,084,320 Text (CSV) and TensorFlow Record files Classification 2017 [148] J. Gemmeke et al., Google Bird Audio Detection challenge Audio from environmental monitoring stations, plus crowdsourced recordings 17,000+ Classification 2016 (2018) [149] [150] Queen Mary University and IEEE Signal ...
1.6.2 US$38.90 / Free trial version No Proprietary: Sente Third Street Software, Inc. 2004 Shut down in 2017 6.7.9 US$60–80 [a] / Free for libraries up to 100 refs No Proprietary: Desktop and iPad, centralized backup/synching; discontinued WizFolio: WizPatent 2008-06 Shut down in 2017 Avatara US$25 / Free Basic version No Proprietary
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 ...
Tab-separated values (TSV) is a simple, text-based file format for storing tabular data. [3] Records are separated by newlines, and values within a record are separated by tab characters. The TSV format is thus a delimiter-separated values format, similar to comma-separated values.
1983, Lotus 1-2-3 for MS-DOS, the first killer application for the IBM PC, it took the market from Visicalc in the early 1980s. 1983, Dynacalc for OS-9 a Unix-like operating system, similar to VisiCalc. [11] 1984, Lotus Symphony for MS-DOS, the follow-on to Lotus 1-2-3; 1985, Boeing Calc for MVS and MS-DOS, written by subsidiary of aviation ...
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
Normalization: map values to numbers, the input can be continuous or discrete. Discretization: map continuous values to discrete values. Value mapping: map discrete values to discrete values. Functions (custom and built-in): derive a value by applying a function to one or more parameters. Aggregation: used to summarize or collect groups of values.
There have been some efforts to define standards for the data mining process, for example, the 1999 European Cross Industry Standard Process for Data Mining (CRISP-DM 1.0) and the 2004 Java Data Mining standard (JDM 1.0). Development on successors to these processes (CRISP-DM 2.0 and JDM 2.0) was active in 2006 but has stalled since.