Row 7938
Content Data
This page contains data entry 7938 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
\[Goodfellow\] In the chapter 6 (feedforward) there is an argument towards linear models being weak that is, \`\`Linear models also have the obvious defect that the model capacity is limited to linear functions, so the model cannot understand the interaction between any two input variables.\`\` How is this true?
Here is what I think about this, the linear models are linear with respect to the parameters. Now In case I want to learn any interaction between 2 variables say `f(x1, x2)` then I can simply add this as a new feature in my dataset for every sample and apply linear regression. Wouldn't this make the statement by Goodfellow wrong? What am I missing?
| Field | Value |
|---|---|
| text | \[Goodfellow\] In the chapter 6 (feedforward) there is an argument towards linear models being weak that is, \`\`Linear models also have the obvious defect that the model capacity is limited to linear functions, so the model cannot understand the interaction between any two input variables.\`\` How is this true? Here is what I think about this, the linear models are linear with respect to the parameters. Now In case I want to learn any interaction between 2 variables say `f(x1, x2)` then I can … |
| label | r/deeplearning |
| dataType | post |
| communityName | r/deeplearning |
| datetime | 2024-05-18 |
| username_encoded | Z0FBQUFBQm5LakwzeEhoM3l3YktXMWhzLXZHSGNjVGdoQ1dQeHRELVc0UzJHSnRwSHF2c0JaNzk1WDJublZTSURfTVJKcWNhYnRmSlNabFBSelpZTng5dHM3VGFvbzkwSVBnRG12ejRBTUM5Y09QeVRENGJrcTg9 |
| url_encoded | Z0FBQUFBQm5Lak9IYk5hUDFEVGgwQ0I5MW9uZXItTWw3QS01OFFhQkJvc3N4OFIybTE1Q21xc2QxSXIxUGZRZ002WXJ4TWFYT09PSFdscnBYQlhmZ1FtZ0k5WmNhSWl4b18zZ3F1VERLaDk0Wl8tcEJHeHhQckE2TnQ2ejM4S3JMZ1k1dFpRTXhGMmVQZG10OC1jT3FBMDB4MzBpTGFsOXNsUVRMMGpoMmlQYUtPS2FUQkpvZnBQbW8yNURrNThDR1JmcHJ1OUYzNE9Zck5CeEFlS3NLRm9PTEtIWVZBcEJTdz09 |
Raw Record
{
"text": "\\[Goodfellow\\] In the chapter 6 (feedforward) there is an argument towards linear models being weak that is, \\`\\`Linear models also have the obvious defect that the model capacity is limited to linear functions, so the model cannot understand the interaction between any two input variables.\\`\\` How is this true?\n\nHere is what I think about this, the linear models are linear with respect to the parameters. Now In case I want to learn any interaction between 2 variables say `f(x1, x2)` then I can simply add this as a new feature in my dataset for every sample and apply linear regression. Wouldn't this make the statement by Goodfellow wrong? What am I missing?",
"label": "r/deeplearning",
"dataType": "post",
"communityName": "r/deeplearning",
"datetime": "2024-05-18",
"username_encoded": "Z0FBQUFBQm5LakwzeEhoM3l3YktXMWhzLXZHSGNjVGdoQ1dQeHRELVc0UzJHSnRwSHF2c0JaNzk1WDJublZTSURfTVJKcWNhYnRmSlNabFBSelpZTng5dHM3VGFvbzkwSVBnRG12ejRBTUM5Y09QeVRENGJrcTg9",
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}
Entry Information
- Entry ID: 7938
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000