sklearn | 数据挖掘库sklearn的使用教程和demo

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kandi X-RAY | sklearn Summary

sklearn is a Python library. sklearn has no bugs, it has no vulnerabilities and it has low support. However sklearn build file is not available. You can download it from GitHub.

数据挖掘库sklearn的使用教程和demo

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Quality

Security

License

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Support

sklearn has a low active ecosystem.

It has 50 star(s) with 49 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

sklearn has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sklearn is current.

Quality

sklearn has 0 bugs and 0 code smells.

Security

sklearn has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

sklearn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

sklearn 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.

Reuse

sklearn releases are not available. You will need to build from source code and install.

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

sklearn saves you 676 person hours of effort in developing the same functionality from scratch.

It has 1567 lines of code, 9 functions and 37 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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sklearn Key Features

No Key Features are available at this moment for sklearn.

sklearn Examples and Code Snippets

No Code Snippets are available at this moment for sklearn.

Community Discussions

Trending Discussions on sklearn

How to test all possible iterations in a multiple linear regresion and return the best R-Squared and P values combination

Pandas RMSE Groupby Multiple Conditions

How to use database models in Python Flask?

SHAP DeepExplainer with TensorFlow 2.4+ error

Keras model not compiling

How to get indices of instances during cross-validation

From train test split to cross validation in sklearn using pipeline

Simultaneous feature selection and hyperparameter tuning

" samples: %r" % [int(l) for l in lengths]) ValueError: Found input variables with inconsistent numbers of samples: [219870, 0, 0]

Group keys within a dictionary based on their similarity

QUESTION

How to test all possible iterations in a multiple linear regresion and return the best R-Squared and P values combination

Asked 2021-Jun-15 at 20:33

I am trying to get the best combination to reach the best R Squared and P value. In this case, I have 6 columns to run the code, but I have the R-Squared and P values just for this combo ([col0, col1, col2, col3, col4, col5] vs [col6]). I want to test all the possible combinations, something like:

[col0] vs [col6]

[col0 + col1] vs [col6]

[col0 + col1 + col2] vs [col6]...

Is there any way to automatize this? So I dont have to run all possible combinations on hand.

...

ANSWER

Answered 2021-Jun-15 at 20:33

What you're looking to implement is the powerset function shown in the iterools documentation:

Source https://stackoverflow.com/questions/67992739

QUESTION

Pandas RMSE Groupby Multiple Conditions

Asked 2021-Jun-15 at 17:13

I am trying to compute the RMSE of a panda dataframe based on multiple conditions: (plant_name, year, month). My datafram (df3m) looks like this:

...

ANSWER

Answered 2021-Jun-15 at 17:13

You can use .GroupBy.apply() and put the call to mean_squared_error inside it, as follows:

Source https://stackoverflow.com/questions/67990261

QUESTION

How to use database models in Python Flask?

Asked 2021-Jun-15 at 02:32

I'm trying to learn Flask and use postgresql with it. I'm following this tutorial https://realpython.com/flask-by-example-part-2-postgres-sqlalchemy-and-alembic/, but I keep getting error.

...

ANSWER

Answered 2021-Jun-15 at 02:32

I made a new file database.py and defined db there.

database.py

Source https://stackoverflow.com/questions/67976688

QUESTION

SHAP DeepExplainer with TensorFlow 2.4+ error

Asked 2021-Jun-14 at 14:52

I'm trying to compute shap values using DeepExplainer, but I get the following error:

keras is no longer supported, please use tf.keras instead

Even though i'm using tf.keras?

...

ANSWER

Answered 2021-Jun-14 at 14:52

TL;DR

Add tf.compat.v1.disable_v2_behavior() at the top for TF 2.4+

calculate shap values on numpy array, not on df

Full reproducible example:

Source https://stackoverflow.com/questions/66814523

QUESTION

Keras model not compiling

Asked 2021-Jun-14 at 07:01

I am trying to build a Keras model for a classification model and I get and error while I am trying to fit the data.

ValueError: Shapes (None, 99) and (None, 2) are incompatible

Code:

...

ANSWER

Answered 2021-Jun-14 at 07:01

The no. of units in the last Dense layer must match the dimensionality of the outputs.

Source https://stackoverflow.com/questions/67964504

QUESTION

How to get indices of instances during cross-validation

Asked 2021-Jun-13 at 17:04

I am doing a binary classification. May I know how to extract the real indexes of the misclassified or classified instances of the training data frame while doing K fold cross-validation? I found no answer to this question here.

I got the values in folds as described here:

...

ANSWER

Answered 2021-Jun-13 at 17:04

From cross_val_predict you already have the predictions. It's a matter of subsetting your data frame where the predictions are not the same as your true label, for example:

Source https://stackoverflow.com/questions/67956643

QUESTION

From train test split to cross validation in sklearn using pipeline

Asked 2021-Jun-13 at 15:49

I have the following piece of code:

...

ANSWER

Answered 2021-Jun-13 at 15:49

Pipeline is used to assemble several steps such as preprocessing, transformations, and modeling. StratifiedKFold is used to split your dataset to assess the performance of your model. It is not meant to be used as a part of the Pipeline as you do not want to perform it on new data.

Therefore it is normal to perform it out of the pipeline's structure.

Source https://stackoverflow.com/questions/67956414

QUESTION

Simultaneous feature selection and hyperparameter tuning

Asked 2021-Jun-13 at 14:19

I'm trying to conduct both hyperparameter tuning and feature selection on a sklearn SVC model.

I tried the below code, but am getting an error which I have included.

...

ANSWER

Answered 2021-Jun-13 at 14:19

You want to perform a grid search over a Pipeline object. When defining the parameters for the different steps of the pipeline, you have to use the __ syntax:

Source https://stackoverflow.com/questions/67958533

QUESTION

" samples: %r" % [int(l) for l in lengths]) ValueError: Found input variables with inconsistent numbers of samples: [219870, 0, 0]

Asked 2021-Jun-12 at 20:22

I'm trying to train some ML algorithms on some data that I collected, but I received an error for input variables with inconsistent numbers of samples. I'm not really sure what variables needs to be changed or not. I've posted my code below to give you a better understanding of what I'm trying to accomplish:

...

ANSWER

Answered 2021-Jun-12 at 12:14

The file has to be opened in binary mode.

open(DATA_FILE, 'rb')

Source https://stackoverflow.com/questions/67948722

QUESTION

Group keys within a dictionary based on their similarity

Asked 2021-Jun-12 at 19:44

I would like to group keys in a dictionary based on their respective similarity. I want to look for similarity within different keys, and if they are similar enough, group them. Probably by using some sort of similarity score. I am thus specifically not interested in how they values within those dictionary match up (in the example below I kept them the same). I have been looking at similarity scores using sklearn cosine_similarity, but I could not find a way to apply this to keys in a dictionary. Anyone any clues on this?

I made a test dictionary to show what I mean. Some keys are very similar, and I would like to group those. How to group those is beyond the point now, but let's say I would like to add the numbers up.

As always, many thanks!

...

ANSWER

Answered 2021-Jun-12 at 19:44

You can't calculate cosine similarity between strings. You can either calculate the pairwise string distance and cluster on that or using tf-idf on character n-grams, see this post for a similar discussion. In your case, we can try this:

Source https://stackoverflow.com/questions/67924447

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

Vulnerabilities

No vulnerabilities reported

Install sklearn

You can download it from GitHub.
You can use sklearn 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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