How to code Affine Transform in TensorFlow 2.0 that can work for digital images?
I've tried tf.keras.preprocessing.image.apply_affine_transform from TensorFlow 1.14 but TensorFlow 2.0 has no such transform. Now I need it for TensorFlow 2.0.
The comment of #lanery leads me to the answer provided by tensorflow here
This was not avaiable in 1.4 < tensorflow <= 2.3
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Hey Folks looking to map pyspark and sklearn gradient boosting regressorss parameters.
What is the sklearn equivalent of maxIter and minInfoGain ?
I read through the documentation and tried using chat gpt
GPflow seems to only support multi-output for SVGP. Is it possible to use this multi-output support for other models (e.g. SGPR)? For example:
kernel = mk.SharedIndependentMok(gpf.kernels.RBF(D), P)
feature = features.InducingPoints(X[:M,...].copy())
m = gpf.models.SGPR(X, Y, kernel, feature)
This is an identified issue (https://github.com/GPflow/GPflow/issues/1209), that currently has comparatively low priority for the GPflow core developers - but we'd be very happy for you to join us and contribute features! There is now a public GPflow slack for ease of discussion.
I have a .h5 file I want to upload to Matlab using the import tool for TensorFlow in matlab, like this:
layers = importKerasLayers('myModel.h5');
But I get the following error:
Option to import Keras networks containing LSTM layers is not yet
supported.
layers =importKerasLayers('myModel.h5');
I've tried this in 2018a, and apperantly all layers related to LSTM are available in this version after the toolbox is downloaded, but I keep getting the error. In this link, you can see the toolbox has support for LSTM layers, but not sure what's causing the error then.
Is there any workaround to solve this? What could be causing the error?
Your link is for R2018b documentation. This is the R2018a documentation and it shows no support for LSTM! So probably switch versions and try!
I have MATLAB 2017b. I see that matlab has recently included a function ranova for repeated measures anova, but whenever I want to use it, the following message is returned:
>> ranova(Accuracies)
Undefined function or variable 'ranova'.
Is there a specific toolbox I would need, or what is the problem?
This ones are the ones I have:
MATLAB Version 9.3 (R2017b)
Simulink Version 9.0 (R2017b)
Bioinformatics Toolbox Version 4.9 (R2017b)
Matlab Toolbox for Dimensionality Reduction Version 0.8
Optimization Toolbox Version 8.0 (R2017b)
Statistics and Machine Learning Toolbox Version 11.2 (R2017b)
I ran a multi-class Logistic Regression with Spark but I would like to use
SVM to cross validate results.
It looks like Spark 1.6 only supports SVM binary classifications. Should I use other tools to do this? H20 for example?
After some research, I found this branch which was not integrated in Spark 1.6 that allowed me to run the SVM on a multi class classification problem.
Big thanks to Bekbolatov.
The commit can be ofund here:
https://github.com/Bekbolatov/spark/commit/463d73323d5f08669d5ae85dc9791b036637c966