Is there a Tableau Desktop executable inside the Tableau server installation.
I have a system where Tableau server in Cloud and would want to use Tableau Desktop in the same... moreIs there a Tableau Desktop executable inside the Tableau server installation.
I have a system where Tableau server in Cloud and would want to use Tableau Desktop in the same server? Is that feasible?
I am trying to do a list report with about 40 columns(Dims+measure) but not able to get it right, the requirement pushes the Tableau limitation by exploiting its limit to only 16... moreI am trying to do a list report with about 40 columns(Dims+measure) but not able to get it right, the requirement pushes the Tableau limitation by exploiting its limit to only 16 columns.How can I get this done?
I want to do a linear regression in R using the lm() function. My data is an annual time series with one field for year (22 years) and another for state (50 states). I want to fit... moreI want to do a linear regression in R using the lm() function. My data is an annual time series with one field for year (22 years) and another for state (50 states). I want to fit a regression for each state so that at the end I have a vector of lm responses. I can imagine doing for loop for each state then doing the regression inside the loop and adding the results of each regression to a vector. That does not seem very R-like, however. In SAS I would do a 'by' statement and in SQL I would do a 'group by'. What's the R way of doing this? less
I want to produce 100 random numbers with normal distribution (with µ=10, σ=7) and then draw a quantity diagram for these numbers.How can I produce random numbers with a... moreI want to produce 100 random numbers with normal distribution (with µ=10, σ=7) and then draw a quantity diagram for these numbers.How can I produce random numbers with a specific distribution in Excel 2010?One more question:When I produce, for example, 20 random numbers with RANDBETWEEN(Bottom,Top), the numbers change every time the sheet recalculates. How can I keep this from happening?
Is there a convenient way to calculate percentiles for a sequence or single-dimensional numpy array?
I am looking for something similar to Excel's percentile function.
I looked in... moreIs there a convenient way to calculate percentiles for a sequence or single-dimensional numpy array?
I am looking for something similar to Excel's percentile function.
I looked in NumPy's statistics reference, and couldn't find this. All I could find is the median (50th percentile), but not something more specific.
I have PyTorch installed in my machine but whenever I try to do the following-
from torchtext import data
from torchtext import datasets
I get the following... moreI have PyTorch installed in my machine but whenever I try to do the following-
from torchtext import data
from torchtext import datasets
I get the following error.
ImportError: No module named 'torchtext'
How can I install torchtext?
For example, I have 1D vector with dimension (5). I would like to reshape it into 2D matrix (1,5).
Here is how I do it with numpy
>>> import numpy as np
>>> a =... moreFor example, I have 1D vector with dimension (5). I would like to reshape it into 2D matrix (1,5).
Here is how I do it with numpy
>>> import numpy as np
>>> a = np.array()
>>> a.shape
(5,)
>>> a = np.reshape(a, (1,5))
>>> a.shape
(1, 5)
>>> a
array()
>>>
But how can I do that with Pytorch Tensor (and Variable). I don't want to switch back to numpy and switch to Torch variable again, because it will loss backpropagation information.
Here is what I have in Pytorch
>>> import torch
>>> from torch.autograd import Variable
>>> a = torch.Tensor()
>>> a
1
2
3
4
5
>>> a.size()
(5L,)
>>> a_var = variable(a)
>>> a_var = Variable(a)
>>> a_var.size()
(5L,)
.....do some calculation in forward function
>>> a_var.size()
(5L,)
Now I want it size to be (1, 5). How can I resize or reshape the dimension of pytorch tensor in Variable without loss grad information. (because I will feed into another model before... less
Is there any way, I can print the summary of a model in PyTorch like model.summary() method does in Keras as follows?
Model... moreIs there any way, I can print the summary of a model in PyTorch like model.summary() method does in Keras as follows?
Model Summary:
____________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
====================================================================================================
input_1 (InputLayer) (None, 1, 15, 27) 0
____________________________________________________________________________________________________
convolution2d_1 (Convolution2D) (None, 8, 15, 27) 872 input_1
____________________________________________________________________________________________________
maxpooling2d_1 (MaxPooling2D) (None, 8, 7, 27) 0 convolution2d_1 ... less
I have been using the introductory example of matrix multiplication in TensorFlow.
matrix1 = tf.constant()
matrix2 = tf.constant(,)
product = tf.matmul(matrix1,... moreI have been using the introductory example of matrix multiplication in TensorFlow.
matrix1 = tf.constant()
matrix2 = tf.constant(,)
product = tf.matmul(matrix1, matrix2)
When I print the product, it is displaying it as a Tensor object:
<tensorflow.python.framework.ops.Tensor object at 0x10470fcd0>
But how do I know the value of product?The following doesn't help:
print product
Tensor("MatMul:0", shape=TensorShape(), dtype=float32)
I know that graphs run on Sessions, but isn't there any way I can check the output of a Tensor object without running the graph in a session? less
I've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the following error:
Error in confusionMatrix.default(predictionsTree,... moreI've trained a tree model with R caret. I'm now trying to generate a confusion matrix and keep getting the following error:
Error in confusionMatrix.default(predictionsTree, testdata$catgeory) : the data and reference factors must have the same number of levels
prob <- 0.5 #Specify class split
singleSplit <- createDataPartition(modellingData2$category, p=prob,
times=1, list=FALSE)
cvControl <- trainControl(method="repeatedcv", number=10, repeats=5)
traindata <- modellingData2
testdata <- modellingData2
treeFit <- train(traindata$category~., data=traindata,
trControl=cvControl, method="rpart", tuneLength=10)
predictionsTree <- predict(treeFit, testdata)
confusionMatrix(predictionsTree, testdata$catgeory)
The error occurs when generating the confusion matrix. The levels are the same on both objects. I cant figure out what the problem is. Their structure and levels are given below. They should be the same. Any help would be greatly appreciated as its... less
There doesn't seem to be too many options for deploying predictive models in production which is surprising given the explosion in Big Data.
I understand that the open-source PMML... moreThere doesn't seem to be too many options for deploying predictive models in production which is surprising given the explosion in Big Data.
I understand that the open-source PMML can be used to export models as an XML specification. This can then be used for in-database scoring/prediction. However it seems that to make this work you need to use the PMML plugin by Zementis which means the solution is not truly open source. Is there an easier open way to map PMML to SQL for scoring?
Another option would be to use JSON instead of XML to output model predictions. But in this case, where would the R model sit? I'm assuming it would always need to be mapped to SQL...unless the R model could sit on the same server as the data and then run against that incoming data using an R script?
Any other options out there? less
Given a vector of scores and a vector of actual class labels, how do you calculate a single-number AUC metric for a binary classifier in the R language or in simple English?
Page... moreGiven a vector of scores and a vector of actual class labels, how do you calculate a single-number AUC metric for a binary classifier in the R language or in simple English?
Page 9 of "AUC: a Better Measure..." seems to require knowing the class labels, and here is an example in MATLAB where I don't understand
R(Actual == 1))
Because R (not to be confused with the R language) is defined a vector but used as a function?
I have a machine learning classification problem with 80% categorical variables. Must I use one hot encoding if I want to use some classifier for the classification? Can i pass... moreI have a machine learning classification problem with 80% categorical variables. Must I use one hot encoding if I want to use some classifier for the classification? Can i pass the data to a classifier without the encoding?
I am trying to do the following for feature selection:
I read the train file:
num_rows_to_read = 10000
train_small = pd.read_csv("../../dataset/train.csv", nrows=num_rows_to_read)
I change the type of the categorical features to 'category':
non_categorial_features =
for categorical_feature in list(train_small.columns):
if categorical_feature not in non_categorial_features:
train_small = train_small.astype('category')
I use one hot encoding
train_small_with_dummies = pd.get_dummies(train_small, sparse=True)
The problem is that the 3'rd part often get stuck, although I am using a strong machine.
Thus, without the one hot encoding I can't do any feature selection, for determining the importance of the features.
What do you recommend?
Can I extract the underlying decision-rules (or 'decision paths') from a trained tree in a decision tree as a textual list?
Something like:
if A>0.4 then if B<0.2 then if... moreCan I extract the underlying decision-rules (or 'decision paths') from a trained tree in a decision tree as a textual list?
Something like:
if A>0.4 then if B<0.2 then if C>0.8 then class='X'
from your experience, which is the most effective approach to implement artificial neural networks prototypes? It is a lot of hype about R (free, but I didn't work with it) or... morefrom your experience, which is the most effective approach to implement artificial neural networks prototypes? It is a lot of hype about R (free, but I didn't work with it) or Matlab (not free), another possible choice is to use a language like C++/Java/C#. The question is mainly targeting the people that tried to test some neural networks architectures or learning algorithms.
If your choice is to use a programming language different from the three mentioned above, can you tell me their names and some explanations concerning your choice (excepting: this is the only/most used language known by me). less
If I want to use the BatchNormalization function in Keras, then do I need to call it once only at the beginning?
I read this documentation for... moreIf I want to use the BatchNormalization function in Keras, then do I need to call it once only at the beginning?
I read this documentation for it: http://keras.io/layers/normalization/
I don't see where I'm supposed to call it. Below is my code attempting to use it:
model = Sequential()
keras.layers.normalization.BatchNormalization(epsilon=1e-06, mode=0, momentum=0.9, weights=None)
model.add(Dense(64, input_dim=14, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.5))
model.add(Dense(64, init='uniform'))
model.add(Activation('tanh'))
model.add(Dropout(0.5))
model.add(Dense(2, init='uniform'))
model.add(Activation('softmax'))
In MNIST LSTM examples, I don't understand what "hidden layer" means. Is it the imaginary-layer formed when you represent an unrolled RNN over time?
Why is the num_units =... moreIn MNIST LSTM examples, I don't understand what "hidden layer" means. Is it the imaginary-layer formed when you represent an unrolled RNN over time?
Why is the num_units = 128 in most cases ?
I trained my CNN (VGG) through google colab and generated .h5 file. Now problem is, I can predict my output successfully through google colab but when i download that .h5 trained... moreI trained my CNN (VGG) through google colab and generated .h5 file. Now problem is, I can predict my output successfully through google colab but when i download that .h5 trained model file and try to predict output on my laptop, I am getting error when loading the model.
Here is the code:
import tensorflow as tf
from tensorflow import keras
import h5py