decision_tree | Ruby Decision Tree / Rules / Workflow Gem | Rule Engine library

by jobready Ruby Version: v0.1.1 License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | decision_tree Summary

decision_tree is a Ruby library typically used in Institutions, Learning, Administration, Public Services, Server, Rule Engine applications. decision_tree has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Ruby Decision Tree / Rules / Workflow Gem

Support

Quality

Security

License

Reuse

Support

decision_tree has a low active ecosystem.

It has 5 star(s) with 2 fork(s). There are 42 watchers for this library.

It had no major release in the last 12 months.

decision_tree has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of decision_tree is v0.1.1

Quality

decision_tree has no bugs reported.

Security

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

License

decision_tree is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

decision_tree releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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decision_tree Key Features

No Key Features are available at this moment for decision_tree.

decision_tree Examples and Code Snippets

Decision Tree,Usage

Ruby

Lines of Code : 50

License : Permissive (MIT)

Copy

class TestWorkflow < DecisionTree::Workflow
  def decision_method
    true
  end

  def reviewed_by_staff
    true
  end

  decision :decision_method do
    yes { it_returned_true }
    no { it_returned_false }
  end

  start do
    decision_metho

Decision Tree,Storing Steps

Ruby

Lines of Code : 38

License : Permissive (MIT)

Copy

class Change < ActiveRecord::Base
  has_many :workflow_steps, as: :workflowable

  def store_steps!(steps)
    workflow_steps.destroy_all

    steps.each_with_index do |step, position|
      new_step = WorkflowStep.from_decision_step(step, self, p

Decision Tree,Storing Steps,Explicit Display Values

Ruby

Lines of Code : 9

License : Permissive (MIT)

Copy

workflow_steps:
  entry_point:
    __start_workflow: 'Decision Workflow Started'
    reviewed_by_etd!: 'ETD has reviewed the provided evidence'
  idempotent_call:
    mark_for_review!: 'Waiting on ETD to review evidence'
  approval_only_required_from

Community Discussions

Trending Discussions on decision_tree

AttributeError and TypeError using CustomTransformers

KeyError: "None of [Index([('A','B','C')] , dtype='object')] are in the [columns]

Not able to plot tree from pipeline

Saving plots to memory rather than disk for python web app

How to capture the names of multiple arguments (...) passed to a function?

AttributeError: module 'pydotplus' has no attribute 'graph_from_dot_data'

Plotting decision tree results from tidymodels

Sagemaker Training Job Not Uploading/Saving Training Model to S3 Output Path

How to update tuning parameter values using the update function in Tidymodels

Sklearn 'numpy.int64' object has no attribute 'columns'

QUESTION

AttributeError and TypeError using CustomTransformers

Asked 2021-May-17 at 18:38

I am building a model using customized transformers (KeyError: "None of [Index([('A','B','C')] , dtype='object')] are in the [columns]). When I run the below code, I get an error because of .fit:

...

ANSWER

Answered 2021-May-17 at 18:38

A common error in text transformers of sklearn involves the shape of the data: unlike most other sklearn preprocessors, text transformers generally expect a one-dimensional input, and python's duck-typing causes weird errors from both arrays and strings being iterables.

Your TextTransformer.transform returns X[['Tweet']], which is 2-dimensional, and will cause problems with the subsequent CountVectorizer. (Converting to a numpy array with .values doesn't change the dimensionality problem, but there's also no compelling reason to do that conversion.) Returning X['Tweet'] instead should cure that problem.

Source https://stackoverflow.com/questions/67572787

QUESTION

KeyError: "None of [Index([('A','B','C')] , dtype='object')] are in the [columns]

Asked 2021-May-17 at 13:18

I defined my X and y as follows:

...

ANSWER

Answered 2021-May-17 at 13:10

If numeric_columns (and any of the others) are tuples, then you do

Source https://stackoverflow.com/questions/67570123

QUESTION

Not able to plot tree from pipeline

Asked 2021-Apr-03 at 12:52

I have this below code for a decision tree classification, I am able to see results of predictions for this model but not able to draw the tree

...

ANSWER

Answered 2021-Apr-03 at 12:52

There is nothing named decisiontree_entropy_model_clf in your code; to plot the decision tree from the pipeline, you should use

Source https://stackoverflow.com/questions/66929529

QUESTION

Saving plots to memory rather than disk for python web app

Asked 2021-Mar-10 at 23:09

I'm developing a FastAPI application which uses sci-kit learn to generate some SVG files which are saved locally before being uploaded to AWS-S3 for permanent storage. However, once deployed on Heroku I realised it doesn't allow for writing to local storage.

An example of how these files are generated:

...

ANSWER

Answered 2021-Mar-10 at 23:09

Answer is yes it's possible by using StringIO, though S3 requires the object to be in a string(?) like format eg:

Source https://stackoverflow.com/questions/66571496

QUESTION

How to capture the names of multiple arguments (...) passed to a function?

Asked 2021-Jan-13 at 13:58

I have a couple of models that are passed by a function, the number of models is variable. Through (...) I can pass all the models as follows:

...

ANSWER

Answered 2021-Jan-13 at 13:58

You didn't use any names for those arguments. If you had, those would have been part of the result. For example, use

Source https://stackoverflow.com/questions/65703086

QUESTION

AttributeError: module 'pydotplus' has no attribute 'graph_from_dot_data'

Asked 2020-Dec-13 at 15:14

I'm trying to graph an example decision tree based on the article I found from: AttributeError: module 'pydotplus' has no attribute 'Node'. However, I'm still getting an attribute error:

...

ANSWER

Answered 2020-Dec-13 at 15:14

in pydotplus the graph_from_dot_data is in the pydotplus.graphviz package.

use

pydotplus.graphviz.graph_from_dot_data(...)

Source https://stackoverflow.com/questions/65277108

QUESTION

Plotting decision tree results from tidymodels

Asked 2020-Aug-22 at 06:11

I have managed to build a decision tree model using the tidymodels package but I am unsure how to pull the results and plot the tree. I know I can use the rpart and rpart.plot packages to achieve the same thing but I would rather use tidymodels as that is what I am learning. Below is an example using the mtcars data.

...

ANSWER

Answered 2020-Aug-21 at 21:50

The following works (note the extra $fit):

Source https://stackoverflow.com/questions/63527684

QUESTION

Sagemaker Training Job Not Uploading/Saving Training Model to S3 Output Path

Asked 2020-Jul-31 at 21:36

Ok I've been dealing with this issue in Sagemaker for almost a week and I'm ready to pull my hair out. I've got a custom training script paired with a data processing script in a BYO algorithm Docker deployment type scenario. It's a Pytorch model built with Python 3.x, and the BYO Docker file was originally built for Python 2, but I can't see an issue with the problem that I am having.....which is that after a successful training run Sagemaker doesn't save the model to the target S3 bucket.

I've searched far and wide and can't seem to find an applicable answer anywhere. This is all done inside a Notebook instance. Note: I am using this as a contractor and don't have full permissions to the rest of AWS, including downloading the Docker image.

Dockerfile:

...

ANSWER

Answered 2020-Jul-29 at 03:20

Have you tried saving to a local file and moving it to S3? I would save it locally (to the root directory of the script) and upload it via boto3.

The sagemaker session object may not have a bucket attributes initialized. Doing it explicitly isn't much an extra step.

Source https://stackoverflow.com/questions/63145277

QUESTION

How to update tuning parameter values using the update function in Tidymodels

Asked 2020-Jul-26 at 01:54

I tried to override the default tuning values using the update function in tidymodels, but the values failed to get updated.

For example, in the codes below, I would like to change the range of min_n from the default of 2 to 40 to 30 to 50. However, the values of min_n remained at 2 and 40.

...

ANSWER

Answered 2020-Jul-26 at 01:54

The update method returns a new parameters object -- it doesn't update the the value you pass supply in-place. You would need to do

Source https://stackoverflow.com/questions/63095311

QUESTION

Sklearn 'numpy.int64' object has no attribute 'columns'

Asked 2020-Jun-11 at 13:54

I have written a regression model that I want it to predict future bitcoin prices. I'm trying to get it to work but have come across multiple problems. Here is my source code:

...

ANSWER

Answered 2020-Jun-11 at 13:53

date_index is a scalar but you type date_index.columns which raises the error

DETAILS:

Everything works fine until this part of the code:

Source https://stackoverflow.com/questions/62322450

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

Vulnerabilities

No vulnerabilities reported

Install decision_tree

Add this line to your application's Gemfile:.

Support

Fork it ( http://github.com/jobready/decision_tree/fork )Create your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull Request

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