libsvm | LIBSVM for the browser and nodejs fire | Machine Learning library

Iam struggling to understand why the first way works and the second throws error.
Suppose we have this array

I am trying to use LibSVM from weka command line but it gives me error: Error: Could not find or load main class weka.classifiers.functions.LibSVM I tried java -cp weka.jar:LibSVM.jar:"C:\wekafiles\packages\LibSVM\LibSVM.jar":"\wekafiles\packages\LibSVM\lib\libsvm.jar" weka.classifiers.functions.LibSVM -S 0 -K 1 -D 3 -G 0.0 -R 0.0 -N 0.5 -M 40.0 -C 1.0 -E 0.001 -P 0.1 -model D:\Weka-3-8-5 -seed 1 Other ML algorithms works but the one I installed using weka are not working from command line.

Invoking a multimodel Sagemaker Endpoint, I get an error that it is not multimodel. I create it like this.

I wrote a code in eclipse to do something as follows.

1. run svm_train while using an input from output.txt whose data format is libSVM.
2. use cross validation while adding "-v 3" in parameter.
3. show an output from libSVM on console.

I was given assignment to run some code and show results using the Apache Spark using Python Language, I installed the Apache Spark server using the following steps: https://phoenixnap.com/kb/install-spark-on-windows-10. I tried my code and everything was fine. Now I am assigned another assignment, it needs MLlib linear regression and they provide us with some code that should be running then we will add additional code for it. When I try to run the code I have some errors and warnings, part of them appeared in the previous assignment but it still working. I believe the issue is that there are additiona things related to Mlib Library should be added so the code will run correctly. Anybody has any idea what files should be added to the spark so it runs the code related to MLib? I am using Windows 10, and spark-3.0.1-bin-hadoop2.7

This is my code :

I'm trying to install lisp in my laptop by following the instruction command and steps that is suggested this site : https://grishagin.com/lisp/windows10/2017/01/26/install-lisp-Windows10.html. I have done following steps :

1. I've extract emacs in my specified directory and add it's bin path to the system variable PATH

2. I've created a another new directory named C:\HOME and add it system variable with variable HOME and value C:\HOME

3. Clisp 2.48 is installed in my lisp directory and To fix some problem, copied svm.dll out of clisp- 2.48/libsvm directory into clisp-2.48/full.

4. Place quicklisp.lisp into lisp directory and run following code in clisp

   (load "C:/lisp/quicklisp.lisp"), (quicklisp-quickstart:install :path "C:/lisp/quicklisp/")

   this two command worked but when i go from next command : (ql:add-to-init-file) It shows this error :- READ from #: there is no package with name "QL".

Can anyone please help to solve this error and explain how does this all help for lisp to keep working?

Hello I'm a beginner currently working on supervised classification in Google Earth Engine. I can't seem to get past the problem 'image.sampleRegions is not a function'. Here are the script that I use.

IllegalArgumentException: MultilayerPerceptronClassifier_... parameter solver given invalid value auto

I believe I have discovered a bug when loading MultilayerPerceptronClassificationModel in spark 3.0.0, scala 2.1.2 which I have tested and can see is not there in at least Spark 2.4.3, Scala 2.11. .

I am using pyspark on a databricks cluster and importing the library “from pyspark.ml.classification import MultilayerPerceptronClassificationModel”

When running model=MultilayerPerceptronClassificationModel.(“load”) and then model. transform (df) I get the following error: IllegalArgumentException: MultilayerPerceptronClassifier_8055d1368e78 parameter solver given invalid value auto.

This issue can be easily replicated by running the example given on the spark documents: http://spark.apache.org/docs/latest/ml-classification-regression.html#multilayer-perceptron-classifier

Then adding a save model, load model and transform statement as such:

I'm mystified by this curiosity. (I'm using ConcurrentHashMap rather than ConcurrentSkipListSet because the class doesn't implement Comparable.) I've got plenty of free CPUs on the computer and there is no difference between the classes that are run in the stream (other than random number generation). It's suspicious that the even numbers run first (consistently).

Here are the code and output with nRuns=10. I would expect all 10 threads to fire up and run simultaneously (as they usually do in my other uses of ConcurrentHashMap). Could it be due to some static code in LIBSVM that gets called by SvmCrossValidator? That's all I can think of. It seems to me from a basic Java perspective this stream should launch all 10 processes at once.