CTR-Prediction | CTR Prediction original paper and personal study notes | Recommender System library

by duboya Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | CTR-Prediction Summary

CTR-Prediction is a Python library typically used in Artificial Intelligence, Recommender System applications. CTR-Prediction has no bugs, it has no vulnerabilities and it has low support. However CTR-Prediction build file is not available. You can download it from GitHub.

Sharing the CTR Prediction original paper and personal study notes

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Support

CTR-Prediction has a low active ecosystem.

It has 105 star(s) with 31 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 149 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CTR-Prediction is current.

Quality

CTR-Prediction has no bugs reported.

Security

CTR-Prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

CTR-Prediction does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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CTR-Prediction releases are not available. You will need to build from source code and install.

CTR-Prediction has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed CTR-Prediction and discovered the below as its top functions. This is intended to give you an instant insight into CTR-Prediction implemented functionality, and help decide if they suit your requirements.

Preprocess training
Build the dictionary
Build the bounds from the datafile
Return the value for a given key
Feature encoder
Fit the model
Predict for each feature
Evaluate the model
Construct a model function
Batch normalization layer
Load training data
Preprocess the train feature map
Build the graph
Check if the model was previously loaded
Load the Iris dataset
Generate batches of data
Build the tf feature
Test a model
Build an estimator
Train a model
Parse input_fn
Train logistic regression
Set TF environment variables
Run the main function of the base model
Train GradientClassifier
Load dataset
Compute the model metric

Get all kandi verified functions for this library.

CTR-Prediction Key Features

No Key Features are available at this moment for CTR-Prediction.

CTR-Prediction Examples and Code Snippets

No Code Snippets are available at this moment for CTR-Prediction.

Community Discussions

Trending Discussions on CTR-Prediction

Analyse huge csv file in R/Python and sampling X% according to the distribution of the file?

How to test a logistic regression model in R?

QUESTION

Analyse huge csv file in R/Python and sampling X% according to the distribution of the file?

Asked 2020-May-23 at 01:26

I have a large csv file (6 GB) and I want to sample 20% of it.

These 20% should be with same distribution as the large original file.

For example, take Kaggles data: https://www.kaggle.com/c/avazu-ctr-prediction/data

I thought about chunks but how can I get the distribution to be the same?

Tried read_csv, fread but without luck.

Please advise how can I do this? My laptop can't handle 6GB csv file.

...

ANSWER

Answered 2018-Sep-08 at 02:10

It's not clear what you mean by "tried fread, but without luck". Was there a specific error? How much RAM does your laptop have?

On my laptop (with 16GB memory) the file can be read without problems and will take only 3.7GB in RAM when loaded:

Source https://stackoverflow.com/questions/51929945

QUESTION

How to test a logistic regression model in R?

Asked 2017-Mar-27 at 22:12

I'm developing a CTR prediction model for the Kaggle competition (link). I've read in the first 100,000 lines of data from the training set, then further split this into train/test sets at 80/20 by

...

ANSWER

Answered 2017-Feb-21 at 00:04

This is happening because you are including the name of the data frame for each variable in the model formula. Instead, your formula should be:

Source https://stackoverflow.com/questions/42355901

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CTR-Prediction

You can download it from GitHub.
You can use CTR-Prediction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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