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1500 questions
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3 answers

Convolutional Neural Networks layer sizes

I am trying to understand an article Backpropagation In Convolutional Neural Networks But I can not wrap my head around that diagram: The first layer has 3 feature maps with dimensions 32x32. The second layer has 32 feature maps with dimensions…
koryakinp
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Imbalanced data causing mis-classification on multiclass dataset

I am working on text classification where I have 39 categories/classes and 8.5 million records. (In future data and categories will increase). Structure or format of my data is as…
outlier
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2 answers

LSTM Feature selection process

We need to implement a time series problem with the LSTM model. But, while implementing the same, the main challenge I am facing is the feature selection issue. Because our data-set contains 2300 observations and 600 features. And we already know…
Abhishek Saha
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2 answers

Understanding the mathematics of AdaGrad and AdaDelta

I have been building some models for a project, but I can't wrap my head around the math of Adagrad and Adadelta algorithms. I do understand how vanilla gradient descent works and I have written code for making it work successfully. I will be…
Malay Hazarika
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Which algorithm to apply for choosing the right point

Picture below shows 7 points around the origin. One of them has been selected by a human based on rules and experience and is colored red (the one in the lower left quadrant). Now we have over 1000 of these sets of points and for each set a human…
Elmex80s
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How to train data by batch from disk?

I am working on a convolutional neural network for image classification. The training dataset is too large to be loaded on my computer memory (4gb), on top of that I also need to try some augmentation to balance the classes. I am using keras. I have…
Learning is a mess
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How to get predicted class labels in convolution neural network?

I have built a convolutional neural network which is needed to classify the test data into either 0 or 1. I am training the CNN with labels either 0 or 1 but while running the below code I am getting the following result. predictions =…
LIsa
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2 answers

Input for LSTM for financial time series directional prediction

I'm working on using an LSTM to predict the direction of the market for the next day. My question concerns the input for the LSTM. My data is a financial time series $x_1 \ldots x_t$ where each $x_i$ represents a vector of features for day $i$, i.e…
articuno
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Using NLP to automate the categorization of user description

I have a huge file of customer complaints about the products my company owns and I would like to do a data analysis on those descriptions and tag a category to each of them. For example: I need to figure out the number of complaints on Software and…
SRS
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How does YOLO algorithm detect objects if the grid size is way smaller than the object in the test image?

In YOLO algorithm how do these grids output a prediction if some grids only see a small black portion of the car if the model was trained on datasets with full images?
Rishi Swethan
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How to get a confidence score for predictions?

In a regression problem, is it possible to calculate a confidence/reliability score for a certain prediction given models like XGBoost or Neural Networks?
Henrique Nader
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What is the BLEU score used in Google Brain's "Attention Is All You Need" paper?

Google Brain's Attention Is All You Need paper on sequence-to-sequence translation reports: Our model achieves 28.4 BLEU on the WMT 2014 Englishto-German translation task, improving over the existing best results, including ensembles, by over 2…
Imran
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3 answers

How to train a xgboost model on data that is too big for the memory?

What are the best practices to train xgboost (eXtreme gradient boosting) models on data that is to big to hold it in memory at once? Splitting the data and train multiple models? Are there more elegant solutions?
Soerendip
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Understanding batch normalization

In the paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (here), before explaining the process of batch normalization, the paper tries to explain the issues related with (I am not getting what the…
figs_and_nuts
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What is the difference between concept class and hypothesis

Formal definition that I have seen of concept class is class of all true functions mathematically : $f:X \rightarrow\{0,1\}$ and that of hypothesis is: $h:X \rightarrow\{0,1\}$ But most of the times they are used together. For example in…
user40687
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