FSelector | FSelector quick get Selector by no xml simplification
kandi X-RAY | FSelector Summary
kandi X-RAY | FSelector Summary
欢迎使用 Flyabbit 全家桶. FSelector quick get Selector by no xml.
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Top functions reviewed by kandi - BETA
- Binds this View to the View
- Build a drawable
- Get the gradient drawable
- Returns the set of states
- Initializes the activity
- Initialize viewPager
- Initialize view
- Create a FSelector
- Draws the path
- Calculate the pixel of the stroke width
- Sets the created view
- Internal method to resize the list
- Sets the stroke width
- Sets the stroke color
- Set the bitmap to the current path
- Ensures that the bounds are valid
- Override this method to change the bounds of the view
- Sets the alpha of the view
- Sets the stroke stroke width
- Method show toast
- Inflates the root view
- On createView
- Set the current item
- Initializes this sprite
- Draws the rectangle
- Sets the color filter to be used for painting
FSelector Key Features
FSelector Examples and Code Snippets
Lines of Code : 35
License : No License
Copy 1. with(context or view) //context or view,put view to bind
2. addDrawable(int type) //根据状态添加 drawable
WINDOW_FOCUSED(android.R.attr.state_window_focused),//true，当此activity获得焦点在最前面时显示该图片；false，当没在最前面时显示该图片。
STATE_ENABLED(and FSelector.with(mTvSelectRoundBgText)//mTvSelectRoundBgText 必需为 textview
.addDrawable()
.shapeType(FSelector.OVAL)
.size(dp2px(80), dp2px(80))
.useLevel(true)
.stokeWidth(dp2p allprojects {
repositories {
...
maven { url 'https://jitpack.io' }
}
}
dependencies {
implementation 'com.github.chengzichen:FSelector:release1.0.2'
}
Community Discussions
Trending Discussions on FSelector
QUESTION
I am a beginner on mlr3 and am facing problems while running AutoFSelector learner associated to glmnet on a classification task containing >2000 numeric variables. I reproduce this error while using the simpler mlr3 predefined task Sonar. For note, I am using R version 4.1.2 (2021-11-01)on macOS Monterey 12.1. All required packages have been loaded on CRAN.
...ANSWER
Answered 2022-Jan-24 at 18:05This is a problem specific to glmnet. glmnet requires at least two features to fit a model, but in at least one configuration (the first ones in a sequential forward search) you only have one feature.
There are two possibilities to solve this:
- Open an issue in mlr3fselect and request a new argument
min_features(there already ismax_features) to be able to start the search with 2 or more features. - Augment the base learner with a fallback which gets fitted if the base learner fails. Here is fallback to a simple logistic regression:
QUESTION
required_packs <- c("pdftools","readxl","pdfsearch","tidyverse","data.table","stringr","tidytext","dplyr","igraph","NLP","tm", "quanteda", "ggraph", "topicmodels", "lasso2", "reshape2", "FSelector")
new_packs <- required_packs[!(required_packs %in% installed.packages()[,"Package"])]
if(length(new_packs)) install.packages(new_packs)
i <- 1
for (i in 1:length(required_packs)) {
sapply(required_packs[i],require, character.only = T)
}
ANSWER
Answered 2021-Dec-27 at 20:12I think the problem is that you used T when you meant TRUE. For example,
QUESTION
Recently I was learning about using mlr3 package. I was doing a feature selection and wanted to compare the model results.However, I wonder how to get the model results from a Benchmarkresult, like what features were uesd in the feature selected learner model.
Here is my code:
...ANSWER
Answered 2021-Jun-21 at 14:24Install the latest mlr3fselect version from gh which offers new helper functions.
extract_inner_fselect_results(bmr_Wra)
Returns the best feature sets of the inner resampling loop. Since you are using hold-out validation, it is just one set.
extract_inner_fselect_archives(bmr_Wra)
Returns all evaluated feature sets of the inner resampling loop. Create the AutoTuner with store_models = TRUE, if you want to access the corresponding models which are stored in the ResampleResults.
You might want to read the book chapter on nested resampling.
QUESTION
I'm trying to use SequentialFeatureSelector and for estimator parameter I'm passing it a pipeline that includes a step that inputes the missing values:
ANSWER
Answered 2021-Feb-08 at 21:16ScikitLearn's documentation does not state that the SequentialFeatureSelector works with pipeline objects. It only states that the class accepts an unfitted estimator. In view of this, you could remove the classifier from your pipeline, preprocess X, and then pass it along with an unfitted classifier for feature selection as shown in the example below.
QUESTION
I convert a JInputStream to base64 with a MemoryStream as intermediary. I need to do that because JInputStream doesn't extend the base class TStream.
I deliberately simplified the code by removing the try/finally block.
...ANSWER
Answered 2021-Feb-26 at 20:55Import for the Android Base64 class:
QUESTION
I am learning how to code in R for machine learning. I am using rpart to do the heavy lifting. However, when I go to plot my decision tree, only a leaf node 'yes' is plotted. I've created the decision tree myself by hand using information gain. The tree should have three levels of nodes.
Here is what R gives me.
Here is my R code.
...ANSWER
Answered 2021-Feb-18 at 02:01You are getting a tree with a single node because you are using the default settings for rpart. The documentation is a little indirect. The documentation tells you that there is a parameter called control and says "See rpart.control." If you click through to the documentation for rpart.control, you will see that there is a parameter called minsplit which is described as "the minimum number of observations that must exist in a node in order for a split to be attempted." The default value is 20 and you only have 14 data points altogether. It will not split the root node. Instead, use rpart.control to set minsplit to a lower value (try 2).
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install FSelector
You can use FSelector like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the FSelector component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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