WEKA 3.8 won't run on Win10 - machine-learning

I can run WEKA 3.6.9 on my Win10 machine, but WEKA 3.8.4 fails. The error is ' Could not initialize the GenericPropertiesCreater. This exception was produced: java.lang.NumberFurmatException: For input string:" '
This problem also is blocking the FIJI plugin ' Trainable Weka Segmentation' within FIJI.
I've tried removing all references to WEKA and reinstalling it. Updating Java, WEKA, and FIJI.
I do pro bono rapid prototyping in FIJI for graduate students in medical and engineering/science fields, so please feel free to ask me any questions on image processing or machine learning.
Thanks for any help
Ron DeSpain

Related

OpenCV version compatibility

I'm trying to apply my algorithm (made OpenCV) to the Inspection machine.
but, my develop environment is OpenCV 4.6 (win10). but the machine's env is OpenCV b5a (win XP)
so, we have problem in here.
I know the b5a version is too old.
but We can't the OpenCV version in machine go up. (the soft ware is too heavy to change version)
and the my algorithm include so many OpenCV function. so It is not easy to make without OpenCV function.
Could anyone have a good idea for figure this problem?

Inconsistency for decreasing loss

[x] Check that you are up-to-date with the master branch of Keras. You can update with:
pip install git+git://github.com/fchollet/keras.git --upgrade --no-deps
[x] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found here.
[x] Provide a link to a GitHub Gist of a Python script that can reproduce your issue (or just copy the script here if it is short).
Hello everyone, I have been using this script Python script
The problem is that I am unable to produce similar result everytime.
Sometimes, I can produce a similar result (loss of 0.3~ within 500 epochs) but sometimes I still get a loss of 3.x after 1500epochs. I am not sure if this is a bug or this is because the algorithm just stuck at a local minimum .
Moreover, after I adjusted the close price (without dividing by 100) and I increased the learning rate for 100x, the problem still exists and it stuck at a loss of 30000. Do you guys think there is anything can do to improve the model?
By normalizing the featureset, it works fine now.

can we run digits or caffe on Mac without GPU?

I have seen caffe installation for Mac. But I have a question. If my Mac does not have GPU, then I have no chances to use GPU?? and I have to use CPU-only?
or I have the chance of using (virtual!) GPU by NVIDIA web driver?
Moreover, can I have digits on my Mac? as I try to download it, it does not have any options for Mac download and it is just for Ubuntu!
I am very confused about these questions! Can you please make me clear about these?
The difference in architectures between CPU and GPU does not allow simple transformation of the code written for one architecture to the other. The GPU drivers are specifically written for the GPU architecture and cannot be easily virtualized. On the other hand, some software supports both. This includes OpenGL instructions and caffe (http://caffe.berkeleyvision.org/). NVidia DIGITS is based on caffe and therefore can work without a dedicated GPU (Here the thread how to install on Macs: https://github.com/NVIDIA/DIGITS/issues/88)
According to https://www.github.com/NVIDIA/DIGITS/issues/251 CUDA cannot be run on computers that do not have a dedicated NVidia GPU, but according to How to run my CUDA application on ATI or Intel card in software mode? there is a program gpuocelot that receives CUDA instructions and can work on NVidia GPU, AMD GPU and x86.
In scientific shared computing they wrote separate programs for different devices, e.g. Einstein at Home has four separate programs to find gravitational waves: CPU, NVidia GPU (CUDA), AMD GPU and ARM.
To make DIGITS work you need to
build Caffe with CPU_ONLY and tell DIGITS not to use any GPUs by
running digits-devserver with the --config flag
(https://github.com/NVIDIA/caffe/blob/v0.13.2/Makefile.config.example#L9-L10, https://github.com/NVIDIA/DIGITS/issues/251).
Other possibility:
you can still use the --config flag with the web installer. Try this:
./runme.sh --config. Choose "N" to select none.
Also a possibility:
I am trying to answer how you can choose CPU or GPUs.. Within the
caffe folder, there is a Makefile.config.example file.. Copy the
contents of this file into a new file and rename it as
"Makefile.config". If you want to use CPU, then
1. comment out the "USE_CUDNN :=1 Within "Makefile.config" file,
2. uncomment CPU_ONLY := 1
3. issue the make all command again within the caffe folder..
And if nothing helps you can do the procedure two times because it helped someone at the end of the thread.

Unable to use XMeans in Weka 3-7-5 After Installing Via Package Manager

I am trying to use a clustering algorithm that lets me choose the initial seeds, so I decided to try and use Weka's Xmeans through the weka GUI. However, when I install Xmeans using weka's package manager, it remains greyed out in the GUI, and I am unable to start clustering even after loading in one of weka's provided test.arff files. Can anyone point me into the right direction or suggest another program or java library to accomplish such a task?

Can't find Neo4jImport.bat

I just installed Neo4j 2.2 Milestone 1 Release on a Windows 64-bit machine and I am unable to locate the file Neo3jImport.bat.
I want to play around with the feature described here. Until now, I have been playing around with the RNeo4J package. It has helped the learning curve quite a bit, but now that I am goint beyond toy datasets, importing data using the package is painful.
With that said, I can't seem to locate the file/utility that seemingly makes importing larger datasets a breeze. I was expecting to see the file at C:\Program Files\Neo4j Community\bin.
I imagine this is a really basic question, but I am somewhat stumped.
Thanks in advance.
Sorry for the exclusion but the binary installation misses also Neo4jShell and other command line scripts as is is intended for a UI only user.
Please use the ZIP download from neo4j.com/download as Mark suggested.

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