When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    Instead of trying to make a super-cell that spans rows/columns, split it into smaller cells while leaving some cells intentionally empty. Use a non-breaking space with   or {} in empty cells to maintain the table structure. Custom CSS styling: Override the wikitable class defaults by explicitly specifying: border-collapse: collapse;

  3. Help:Table - Wikipedia

    en.wikipedia.org/wiki/Help:Table

    If all the cells in a row are empty the cells still show up. If the header cell is also empty for that row all the cells show up, but they are narrow. That can be fixed with a simple <br> in one of the cells. That is what is done here:

  4. Google Sheets - Wikipedia

    en.wikipedia.org/wiki/Google_Sheets

    Google Sheets is a spreadsheet application and part of the free, web-based Google Docs Editors suite offered by Google. Google Sheets is available as a web application; a mobile app for: Android, iOS, and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft Excel file formats. [5]

  5. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    CSV is a delimited text file that uses a comma to separate values (many implementations of CSV import/export tools allow other separators to be used; for example, the use of a "Sep=^" row as the first row in the *.csv file will cause Excel to open the file expecting caret "^" to be the separator instead of comma ","). Simple CSV implementations ...

  6. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    Tabular data is two dimensional — data is modeled as rows and columns. However, computer systems represent data in a linear memory model , both in-disk and in-memory. [ 7 ] [ 8 ] [ 9 ] Therefore, a table in a linear memory model requires mapping its two-dimensional scheme into a one-dimensional space.

  7. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    By first clustering unlabeled text data using k-means, meaningful features can be extracted to improve the performance of NER models. For instance, k -means clustering can be applied to identify clusters of words or phrases that frequently co-occur in the input text, which can then be used as features for training the NER model.

  8. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous words or suggest additional words for a partial sentence. Word2vec was developed by Tomáš Mikolov and colleagues at Google and published in 2013.