Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
Categorical variables are very common in a machine learning project. On a high level, there are two ways to handle a categorical variable.
Drop a categorical variable if a categorical variable …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
It is strongly suggested that you load data into a pandas DataFrame
and handle categorical variables
by specifying a dtype of "category" for those categorical variables.
df.cat_var = df.cat_var.astype …Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://arxiv.org/pdf/1206.5533.pdf**
https://towardsdatascience.com/17-rules-of-thumb-for-building-a-neural-network-93356f9930af
https://hackernoon.com/rules-of-thumb-for-deep-learning-5a3b6d4b0138
https://stats.stackexchange.com/questions/181/how-to-choose-the-number-of-hidden-layers-and-nodes-in-a-feedforward-neural-netw
Batch size affects both …
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://en.wikipedia.org/wiki/List_of_datasets_for_machine-learning_research
https://www.nist.gov/
VOC-2012
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
https://www.kaggle.com/c/home-credit-default-risk/discussion/61613
https://studylib.net/doc/18339870/yetirank--everybody-lies
http://proceedings.mlr.press/v14/gulin11a/gulin11a.pdf
| Model | Architecture | Ranking Category | SOTA | Comments | Paper |
|---|---|---|---|---|---|
| RankNet | NN … |
Things on this page are fragmentary and immature notes/thoughts of the author. Please read with your own judgement!
coefficients don't change but variance become smaller. use formula to show it ...
common in computer vision …