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1500 questions
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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
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what machine/deep learning/ nlp techniques are used to classify a given words as name, mobile number, address, email, state, county, city etc

I am trying to generate an intelligent model which can scan a set of words or strings and classify them as names, mobile numbers, addresses, cities, states, countries and other entities using machine learning or deep learning. I had searched for…
Sai Charan Adurthi
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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What is the difference between "expected return" and "expected reward" in the context of RL?

The value of a state $s$ under a certain policy $\pi$, $V^\pi(s)$, is defined as the "expected return" starting from state $s$. More precisely, it is defined as $$ V^\pi(s) = \mathbb{E}\left(R_t \mid s_t = s \right) $$ where $R_t$ can be defined…
user10640
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2 answers

Adding feature leads to worse results

I have a dataset with 20 variables and ~50K observations, I created several new features using those 20 variables. I compare the results of a GBM model (using python xgboost and light GBM) and I found that it doesn't matter what are the…
Yaron
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