Tabular data to image conversion for convolutional neural network applications
Conventionally, machine learning techniques like random forest, decision trees, support vector machines are used for tabular data[1] for classification, identification, or recognition. Tabular data can be in a variety of forms, such as RNA sequencing data, transcriptomics data, statistical data. The sample of tabular data is usually a column vector, which comprises d number of elements or features, also known as dimensionality. The above mentioned machine learning techniques take a column vector and predict or assign it to a target.
On the other hand, the 2D convolutional neural network or simply CNN takes an image as an input and predicts its labels (or provides probabilities). CNN has shown superior performance in many industrial applications. The requirement of having an image input for CNN restricted the analysis of tabular data.[2] Recently, this limitation was overcome through the applications of tabular to image converters[2][3][4] With the help of image converters, CNNs (2D) can be applied for the analysis of tabular data.
References
- ↑ "4 Introduction to Tabular Data". papl.cs.brown.edu. Retrieved 2023-03-11.
- ↑ 2.0 2.1 Sharma, Alok; Vans, Edwin; Shigemizu, Daichi; Boroevich, Keith A.; Tsunoda, Tatsuhiko (2019-08-06). "DeepInsight: A methodology to transform non-image data to an image for convolution neural network architecture". Scientific Reports. 9 (1): 11399. Bibcode:2019NatSR...911399S. doi:10.1038/s41598-019-47765-6. ISSN 2045-2322. PMC 6684600 Check
|pmc=value (help). PMID 31388036. - ↑ Zhu, Yitan; Brettin, Thomas; Xia, Fangfang; Partin, Alexander; Shukla, Maulik; Yoo, Hyunseung; Evrard, Yvonne A.; Doroshow, James H.; Stevens, Rick L. (2021-07-01). "Publisher Correction: Converting tabular data into images for deep learning with convolutional neural networks". Scientific Reports. 11 (1): 14036. Bibcode:2021NatSR..1114036Z. doi:10.1038/s41598-021-93376-5. ISSN 2045-2322. PMC 8249467 Check
|pmc=value (help). PMID 34211076 Check|pmid=value (help). - ↑ Gokhale, Madhuri; Mohanty, Sraban Kumar; Ojha, Aparajita (2023-03-01). "GeneViT: Gene Vision Transformer with Improved DeepInsight for cancer classification". Computers in Biology and Medicine. 155: 106643. doi:10.1016/j.compbiomed.2023.106643. ISSN 0010-4825. PMID 36803792 Check
|pmid=value (help). Unknown parameter|s2cid=ignored (help)
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