parsnip | A modern XML library for Android and Java | Parser library

 by   evant Java Version: Current License: Apache-2.0

kandi X-RAY | parsnip Summary

kandi X-RAY | parsnip Summary

parsnip is a Java library typically used in Utilities, Parser, Gradle applications. parsnip has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.

A modern XML library for Android and Java.
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            kandi-support Support

              parsnip has a low active ecosystem.
              It has 15 star(s) with 3 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 4 open issues and 3 have been closed. On average issues are closed in 36 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of parsnip is current.

            kandi-Quality Quality

              parsnip has 0 bugs and 0 code smells.

            kandi-Security Security

              parsnip has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              parsnip code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              parsnip is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              parsnip releases are not available. You will need to build from source code and install.
              Deployable package is available in Maven.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 12014 lines of code, 235 functions and 59 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed parsnip and discovered the below as its top functions. This is intended to give you an instant insight into parsnip implemented functionality, and help decide if they suit your requirements.
            • Parses an instance of the class
            • Skips next events
            • Returns the field binding with the given name and namespace
            • Returns the field binding for the given name and namespace
            • Create an adapter for the given type
            • Create an adapter method from an object
            • Create an adapter method from an adapter
            • Find and return an adapter for the given type
            • Read tweets from an input stream
            • Extract the PC data from a node
            • Unmarshall the tweets
            • Unmarshalls a node
            • Get the element type of a collection type
            • Get the generic super type
            • Resolve the given type using the given context
            • Initializes the activity
            • Set the progress listener
            • Serializes this tag into the given serializer
            • Initializes the declared namespaces
            • Read Tweets from input stream
            • Invoked afterTaskExecute
            • Returns a string representation of the statistics
            • Returns an array with the key and value pairs of the given context type
            • Converts a value to a media type
            • Waits for the tweets
            • Creates a factory for the given raw type
            Get all kandi verified functions for this library.

            parsnip Key Features

            No Key Features are available at this moment for parsnip.

            parsnip Examples and Code Snippets

            parsnip,Usage,Custom naming
            Javadot img1Lines of Code : 22dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            class BlackjackHand {
              @SerializedName("HiddenCard")
              public final Card hiddenCard;
              @SerializedName("VisibleCard")
              public final List visibleCards;
              ...
            }
            
            class Card {
              public final char rank;
              public final Suit suit;
              ...
            }
            
            enum Suit {
                
            parsnip,Usage,Built in xml adapters
            Javadot img2Lines of Code : 20dot img2License : Permissive (Apache-2.0)
            copy iconCopy
            class BlackjackHand {
              public final Card hiddenCard;
              public final List visibleCard;
              ...
            }
            
            class Card {
              public final char rank;
              public final Suit suit;
              ...
            }
            
            enum Suit {
              CLUBS, DIAMONDS, HEARTS, SPADES;
            }
            
              
            parsnip,License
            Javadot img3Lines of Code : 13dot img3License : Permissive (Apache-2.0)
            copy iconCopy
            Copyright 2015 Evan Tatarka
            
            Licensed under the Apache License, Version 2.0 (the "License");
            you may not use this file except in compliance with the License.
            You may obtain a copy of the License at
            
               http://www.apache.org/licenses/LICENSE-2.0
            
            Unle  

            Community Discussions

            QUESTION

            Creating loop over columns to calculate regression and then compare best combination of variables
            Asked 2022-Mar-24 at 19:14

            I am trying to run a loop which takes different columns of a dataset as the dependent variable and remaining variables as the independent variables and run the lm command. Here's my code

            ...

            ANSWER

            Answered 2022-Mar-24 at 17:53

            We could change the line of fit with

            Source https://stackoverflow.com/questions/71605227

            QUESTION

            Getting more information about C5 model in tidymodels
            Asked 2022-Mar-23 at 20:49

            Here's a simple modelling workflow using the palmerpenguins dataset:

            ...

            ANSWER

            Answered 2022-Mar-23 at 20:49

            Source https://stackoverflow.com/questions/71510155

            QUESTION

            Error in future_map: argument ".f" is missing, with no default
            Asked 2022-Mar-19 at 04:55

            Requesting your help or expert opinion on a parallelization issue I am facing.

            I regularly run an Xgboost classifier model on a rather large dataset (dim(train_data) = 357,401 x 281, dims after recipe prep() are 147,304 x 1159 ) for a multiclass prediction. In base R the model runs in just over 4 hours using registerDoParallel(using all 24 cores of my server). I am now trying to run it in the Tidymodels environment, however, I am yet to find a robust parallelization option to tune the grid.

            I attempted the following parallelization options within tidymodels. All of them seem to work on a smaller subsample (eg 20% data), but options 1-4 fail when I run the entire dataset, mostly due to memory allocation issues.

            1. makePSOCKcluster(), library(doParallel)
            2. registerDoFuture(), library(doFuture)
            3. doMC::registerDoMC()
            4. plan(cluster, workers), doFuture, parallel
            5. registerDoParallel(), library(doParallel)
            6. future::plan(multisession), library(furrr)

            Option 5 (doParallel) has worked with 100% data in the tidymodel environment, however, it takes 4-6 hours to tune the grid. I would request your attention to option 6 (future/ furrr), this appeared to be the most efficient of all methods I tried. This method however worked only once (successful code included below, please note I have incorporated a racing method and stopping grid into the tuning).

            ...

            ANSWER

            Answered 2022-Mar-19 at 04:55

            Apparently, in tidymodels code, the parallelization happens internally, and there is no need to use furrr/future to do manual parallel computation. Moreover, the above code may be syntactically incorrect. For a more detailed explanation of why this is please see this post by mattwarkentin in the R Studio community forum.

            Source https://stackoverflow.com/questions/71506192

            QUESTION

            LASSO regression - Force variables in glmnet with tidymodels
            Asked 2022-Mar-15 at 17:41

            I am doing feature selection using LASSO regression with tidymodels and glmnet.

            It is possible to force variables in glmnet by using the penalty.factors argument (see here and here, for example).

            Is it possible to do the same using tidymodels ?

            ...

            ANSWER

            Answered 2022-Mar-15 at 17:41

            QUESTION

            Why does deploying a tidymodel with vetiver throw a error when there's a variable with role as ID?
            Asked 2022-Mar-11 at 14:46

            I'm unable to deploy a tidymodel with vetiver and get a prediction when the model includes a variable with role as ID in the recipe. See the following error in the image:

            { "error": "500 - Internal server error", "message": "Error: The following required columns are missing: 'Fake_ID'.\n" }

            The code for the dummy example is below. Do I need to remove the ID-variable from both the model and recipe to make the Plumber API work?

            ...

            ANSWER

            Answered 2022-Mar-11 at 14:46

            As of today, vetiver looks for the "mold" workflows::extract_mold(rf_fit) and only get the predictors out to create the ptype. But then when you predict from a workflow, it does require all the variables, including non-predictors. If you have trained a model with non-predictors, as of today you can make the API work by passing in a custom ptype:

            Source https://stackoverflow.com/questions/71397075

            QUESTION

            How can I extract model summary from multiple tidymodels objects using purrr::map functions in R?
            Asked 2022-Jan-20 at 08:40

            I want to use purrr::map_* functions to extract info from multiple models involving linear regression method. I am first creating some random dataset. The dataset has three dependent variables, and one independent variable.

            ...

            ANSWER

            Answered 2022-Jan-20 at 08:40

            The list_tidymodels needs to be created with list() and not with c().

            Source https://stackoverflow.com/questions/70781936

            QUESTION

            Error while predicting a GAM model using tidymodels
            Asked 2022-Jan-12 at 23:47

            WHAT I WANT: I'm trying to fit a GAM model for classification using tidymodels on a given data.

            SO FAR: I'm able to fit a logit model.

            ...

            ANSWER

            Answered 2022-Jan-12 at 23:47

            This problem has been fixed in the developmental version of {parsnip} (>0.1.7). You can install it by running remotes::install_github("tidymodels/parsnip").

            Source https://stackoverflow.com/questions/70682454

            QUESTION

            step_pca() arguments are not being applied
            Asked 2022-Jan-12 at 18:33

            I'm new to tidymodels but apparently the step_pca() arguments such as nom_comp or threshold are not being implemented when being trained. as in example below, I'm still getting 4 component despite setting nom_comp = 2.

            ...

            ANSWER

            Answered 2022-Jan-11 at 14:56

            If you bake the recipe it seems to work as intended but I don't know what you aim to achieve afterward.

            Source https://stackoverflow.com/questions/70667042

            QUESTION

            Block Bootstrapping using Tidymodels
            Asked 2022-Jan-08 at 23:03

            I have a monthly (Jan - Dec) data set for weather and crop yield. This data is collected for multiple years (2002 - 2019). My aim is to obtain bootstrapped slope coefficient of the affect of temperature in each month on yield gap. In bootstrapping, I want to block the year information in a way that the function should randomly sample data from a specific year in each bootstrap rather than choosing rows from mixed years.

            I read some blogs and tried different methods but I am not confident about those. I tried to disect the bootstrapped splits to ensure if I am doing it correctly but I was not.

            Here is the starting code:

            ...

            ANSWER

            Answered 2022-Jan-08 at 04:19

            We don't currently have support for grouped or blocked bootstrapping; we are tracking interest in more group-based methods here.

            If you want to create a resampling scheme that holds out whole groups of data, you might check out group_vfold_cv() (maybe together with nested_cv()?) to see if it fits your needs in the meantime. It results in a resampling scheme that looks like this:

            Source https://stackoverflow.com/questions/70428626

            QUESTION

            Preprocessing data with R `recipes` package: how to impute by mode in numeric columns (to fit model with xgboost)?
            Asked 2021-Dec-25 at 07:37

            I want to use xgboost for a classification problem, and two predictors (out of several) are binary columns that also happen to have some missing values. Before fitting a model with xgboost, I want to replace those missing values by imputing the mode in each binary column.

            My problem is that I want to do this imputation as part of a tidymodels "recipe". That is, not using typical data wrangling procedures such as dplyr/tidyr/data.table, etc. Doing the imputation within a recipe should guard against "information leakage".

            Although the recipes package provides many step_*() functions that are designed for data preprocessing, I could not find a way to do the desired imputation by mode on numeric binary columns. While there is a function called step_impute_mode(), it accepts only nominal variables (i.e., of class factor or character). But I need my binary columns to remain numeric so they could be passed to the xgboost engine.

            Consider the following toy example. I took it from this reference page and changed the data a bit to reflect the problem.

            create toy data

            ...

            ANSWER

            Answered 2021-Dec-25 at 07:37

            Credit to user @gus who answered here:

            Source https://stackoverflow.com/questions/70474049

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

            Vulnerabilities

            No vulnerabilities reported

            Install parsnip

            There is also a retrofit converter.

            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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            https://github.com/evant/parsnip.git

          • CLI

            gh repo clone evant/parsnip

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            git@github.com:evant/parsnip.git

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