Most Popular
1500 questions
10
votes
4 answers
How do we standardize arrays with NaN?
I used StandardScaler() to standardize data so far, but this doesn't work with NaNs. None of the other methods I know of (MinMaxScaler, RobustScaler, MaxAbsScaler) work with NaNs either. Are there other methods?
My search results came up with a…
uharsha33
- 331
- 3
- 4
- 8
10
votes
2 answers
Linear Regression and scaling of data
The following plot shows coefficients obtained with linear regression (with mpg as the target variable and all others as predictors).
For mtcars dataset (here and here) both with and without scaling the data:
How do I interpret these results? The…
rnso
- 1,578
- 3
- 18
- 34
10
votes
2 answers
How to plot learning curve and validation curve while using pipeline
I would appreciate if you could let me know in the following example code:
from collections import Counter
from sklearn.datasets import make_classification
from sklearn.model_selection import…
ebrahimi
- 1,307
- 7
- 20
- 40
10
votes
3 answers
Multivariate Time-Series Clustering
I have a streaming data along with timestamp dataset that looks like this:
1.png
Timestamp can be inclusive of "seconds" too, but the data may or may not change every second. it depends on the previous values(rows i.e data which came earlier w.r.t…
Abhinaya Krishna
- 109
- 1
- 1
- 4
10
votes
2 answers
Is this a Q-learning algorithm or just brute force?
I have been playing with an algorithm that learns how to play tictactoe. The basic pseudocode is:
repeat many thousand times {
repeat until game is over {
if(board layout is unknown or exploring) {
move randomly
} else {
move…
Ant Kutschera
- 211
- 1
- 7
10
votes
5 answers
Qualifications for PhD Programs
Yann LeCun mentioned in his AMA that he considers having a PhD very important in order to get a job at a top company.
I have a masters in statistics and my undergrad was in economics and applied math, but I am now looking into ML PhD programs. Most…
bstockton
- 212
- 1
- 8
10
votes
2 answers
Are there neural networks packages that use complex numbers?
Can you build complex (in terms of complex numbers) neural networks in Keras or Tensorflow or something similar?
This would mean the inputs, weights, activation functions, and outputs would all potentially use complex numbers. I know this can be…
Gillespie
- 202
- 1
- 2
- 7
10
votes
2 answers
How can I find out what class each of the columns in the probabilities output correspond to using Keras for a multi-class classification problem?
I'm using transfer learning to build an image recognition model using a pre-trained VGG network in Keras and excluding the final fully-connected layer to get the output weights. I'm then using these output weights to feed into my new model which…
Ryan Chase
- 469
- 2
- 4
- 14
10
votes
2 answers
interpret results of nvidia-smi
Every 1.0s: nvidia-smi Tue Feb 20 12:49:34 2018
Tue Feb 20 12:49:34…
kRazzy R
- 203
- 2
- 7
10
votes
3 answers
Does Tensorflow support a Decision Tree Classifier?
I am trying to implement decision tree classifier to classify my data set. I am using Python. Now it is easy to implement in scikit learn, but how can I implement this in tensorflow.
Taimur Islam
- 941
- 4
- 11
- 17
10
votes
2 answers
Where to find list of Tensorflow pretrained models available in download.tensorflow.org/models
I am trying the find the pretrained models (graph.pd and labels.txt) files for Tensorflow (for all of the Inception versions and MobileNet)
After much searching I found some models in,…
James
- 181
- 1
- 1
- 7
10
votes
1 answer
Difference between Bernoulli and Multinomial Naive Bayes
Here is my understanding of the difference between a Bernoulli and a Multinomial Naive Bayes:
Bernoulli explicitly models the presence/absence of a feature, whereas Multinomial doesn't.
Is there something that I am missing?
Can someone explain why…
Valentin Calomme
- 6,026
- 3
- 21
- 52
10
votes
3 answers
How the embedding layer is trained in Keras Embedding layer
How is the embedding layer trained in Keras Embedding layer?
(say using tensorflow backend, meaning is it similar to word2vec, glove or fasttext)
Assume we do not use a pretrained embedding.
william007
- 775
- 1
- 10
- 20
10
votes
4 answers
Why positive-unlabeled learning?
Machine learning can be divided into several areas: supervised learning, unsupervised learning, semi-supervised learning, learning to rank, recommendation systems, etc, etc.
One such area is PU Learning, where only Positive and Unlabeled instances…
Ricardo Cruz
- 3,410
- 1
- 15
- 34
10
votes
2 answers
How can I detect if an image was photoshopped?
I would like to check JPG files if they were manipulated to change the content.
What I consider NOT photoshopped:
Cropping
Rotating
(Scaling)
Image resolution
Automatic changes smartphones might make
What I consider photoshopping:
Adding a new…
Martin Thoma
- 18,880
- 35
- 95
- 169