Questions tagged [deep-learning]

a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.

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54 views

Would Deep Q Learning work for a finite horizon problem?

I want to apply Deep Q Learning to a problem, which has a clear finite horizon definition, like: $$V(s) = \mathbb{E}[r_1 + r_2]$$ Since the horizon is finite, I do not use reward discounting. My ...
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17 views

Churn rate prediction based on sequencial data

I am trying to build a machine learning model that can predict if a certain user will churn based on its historical static and dynamic data. The data looks like below: ...
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8 views

Spatial deformation in medical MR images

HI fellows I hope everyone will be good I just want to ask that what is spatial deformation and I want to apply this spatial deformation on medical MR images any answer will be helpful. Thanks and ...
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Regression for Deskew Document problem

I am currently at an impasse regarding my regression problem. My goal is to generate a model that rotates correctly an image. My images are documents (invoices for example). Each document is either ...
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2answers
94 views

Tensorflow - simple multi-layer perceptron not stabilizing around mean of normally distributed y-values

I'm building an FX trading model where I'm trying to predict the +/- movement of a currency pair 5 minutes into the future. I've had some promising results adapting the model as a classifier (i.e., ...
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1answer
34 views

Prediction vs causation in a ML project

I am performing a classification task and was able to identify significant predictors (important features using Random Forest) that can help separate the classes or influence the outcome. But I read ...
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2answers
34 views

Which kind of model is better for keyword-set classification?

There exists a similar task that is named text classification. But I want to find a kind of model that the inputs are keyword set. And the keyword set is not from a sentence. For example: ...
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3answers
62 views

Use of Standardizer to handle outliers?

I have a dataset with 60 columns and 5K records. There are few columns which has outliers. I understand that there are multiple approach to handle outliers. Actually I don't wish to drop the data as ...
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1answer
159 views

Is it reasonable that a problem “solved” by a traditional ANN can also be solved by a CNN?

There is a data science numerical problem, which me and my team were able to get an ANN model that predicts down to a 1% MAPE error (with roughly 70000+ trainable parameters). Given the nature of the ...
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20 views

Loss is decreasing but the predictions are not getting well

I am trying to implement a Dependency Parsing model using the transformer model in here with a few changes. On the training, my loss has decreasing trend; but the predictions at the end of 20 epochs ...
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9 views

Train a competitive layer on nonnormalized vectors using LVQ technique

How can we train a competitive layer on non-normalized vectors using LVQ technique ? The net input expression for LVQ networks calculates the distance between the input and each weight vector ...
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1answer
52 views

Issue with predict generator keras

I'm new with keras with tensorflow backend and I'm trying to do transfer learning with pretrained net. The problem is that the accuracy on validation set is very high, around the 90% , but on test set ...
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2answers
68 views

How can we create an label, value detector?

I am trying to implement an text detector using MaskRCNN such that the model detects the label and value as shown in the image below. Detecting the same is easier for fields like page date and order ...
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1answer
20 views

Could GANs be used to augment data?

I want to use GAN for data augmentation but I am confuse what are the pros. and cons. of data augmentation using GAN or why we use data augmentation using GAN compared to other data augmentation ...
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1answer
70 views

How to interpret Shapley value plot for a model?

I was trying to use Shapley value approach for understanding the model predictions. I am trying this on a Xgboost model. My plot ...
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1answer
36 views

What is the effect of KL divergence between two Gaussian distributions as a loss function in neural networks?

In many deep neural networks, especially those based on VAE architecture, a KL divergence term is added to the loss function. The divergence is computed between the estimated Gaussian distribution and ...
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Object re identification through two cameras

I've been recently using the YOLO to detect trucks in images, which turned out really well. My next step is to try to find images of the same truck across the whole set of images I've retrieved ...
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1answer
26 views

How important is the channel order in deep-learning computer vision tasks?

I stumbled across this question while working with OpenCV, which stores color images in BGR order in memory, while most other libraries I know of use RGB order. How important is this difference? ...
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1answer
14 views

Is it possible to decompose a scalar value to a inter-dependent vector neural network?

My data contains a scalar feature $r$, I found this feature is important for training my deep model. My idea is supposing there is a 3-layer MLP $f(x), x \in \mathbb{R}^{n}$, where $n=1$. It outputs a ...
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May I please get to know which paper first proposed/mentioned to use Shannon's entropy in deep learning/machine learning in neural networks?

I have tried to investigate as to who had first mentioned the use of cross-entropy in deep learning -\sum p(X)\log q(X)
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8 views

Structured and unstructured pruning for deep learning models

I was trying to understand structured and unstructured pruning techniques used for deep learning models[link 1][link 2]1. To recap what I have understand that unstructured pruning is based on weight ...
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1answer
43 views

A cross-entropy loss explanation in simple words

Suppose I build a FNN model. The last layer is a classification layer with softmax activation. A cross-entropy loss is used to classify a problems, such as logistic regression. How would I calculate ...
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28 views

Place of backward and its relation with batches in PyTorch

I am implementing a dependency parsing model using PyTorch and little bit confused about the situation that I explained below. When calculating loss and backward the model; I tried different things. ...
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1answer
39 views

How to choose input variables for ML

Let's say I have a huge database with 100K records and 60 columns. Let's say one of the column is "min_p". What I do is apply some logic/rule to determine the output label for this record. Basically I ...
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1answer
42 views

Training a Siamese Neural Network for object similarity assessment

I am training a Siamese neural network with pairs of similar and dissimilar objects. The features of the objects are binary data on whether they contain some properties or not (2048 features per ...
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1answer
33 views

Role of a known predictor in a disease prediction

I am working on finding out whether the patient will develop the disease or not in a hospital. Might be a basic info but I am just sharing it anyway. Usually through historic data, I was able to see ...
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2answers
37 views

Detect malicious GIFs

I was reading this article talking about a form of targeted internet bullying which involves sending flashing images via Twitter to people with epilepsy. I was wondering whether there is a way to ...
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1answer
32 views

which is better : F1-score of 'N' in imbalanced data or 'N+3' in balanced data?

I have a dataset with 4712 records. Label 1 is 1558(33%) and Label 0 is 3154 (67%) a) Currently when I run the model and analysis as is (without sampling techniques), I get an ...
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2answers
70 views

What's a good F1-score in (not) extremely imbalanced dataset?

I have a dataset with around 4.7K focused on binary classification. Class proportion is 33:67. meaning Label 1 is 1558 (33%) and Label 0 is 3154 (67%) of my dataset. Is my dataset imbalanced? some ...
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2answers
54 views

How to get significance level for ranked features?

I am aware of below approaches of feature selection a) Feature Importance methods which are available in tree based models like Random Forest and ...
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1answer
316 views

How to interpret coefficients from logistic regression?

I ran a logistic regression (statsmodel) on my data with 60 features using the below code ...
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1answer
11 views

Truncating float/doubles for reproducibility

I deploy machine learning models (typically GPU) to a variety of environments. I work sort of at the edge of ML R&D and devops, so I am really big into reproducibility, and one thing that drives ...
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1answer
53 views

How to perform Permutation Feature importance?

I am trying to perform feature selection. Currently with Tree based classifiers, even randomly generated column is ranking above some of my real columns. So I was reading about ...
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2answers
47 views

What does many low important feature indicate?

I have a dataset where I am focusing on binary classification problem. In total,I have around 60 features in my dataset When I used Xgboost Feature Importance, I ...
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1answer
31 views

How to get vectors of memory cell & the last output of $LSTM$ in keras?

In this research paper the following paragraph appears, The state of every LSTM model is stored in two fixed-size vectors of real numbers called the memory cells and the last output. Since our ...
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1answer
22 views

What are x variable and y variable in word2vec model if it is supervised learning

What are x variable and y variable in word2vec model if it is supervised learning. In both the flavours- CBOW and skip-gram model. Though some blogs have explained it as unsupervised learning. ...
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2answers
68 views

Why SVM gridsearch takes longer time?

I have a dataset of 5K records and 60 features focussed on binary classification. Please find my code below for SVM paramter tuning. It's running for a longer time than ...
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19 views

Why does streamlit effect Keras callback code?

I use Streamlit for an image classification project in Keras. I defined a lambda callback: ...
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1answer
17 views

Multiply Tensorflow sequential layer by fixed integers

I'm trying to make a simple reinforcement learning model that makes one of three decisions, A, B, or ...
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27 views

Computer vision and Augmented reality

I'm new to the Computer Vision I want to make AR application, I don't know where to start. Please give me some advice?
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2answers
77 views

How to yield better AUC score?

I have a dataset with 5K records and 60 features focused on binary classification. Class proportion is 33:67 Currently I am trying to increase the performance of my model which is stuck at F1-score ...
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0answers
25 views

Creating deformed convolution using attention mask in Keras

I wanted to create deformable convolution network in Keras and compare its performance with standard convolution in Keras. I tried on MNIST fashion data set. Code for Standard convolution in its ...
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1answer
30 views

Different hidden layer architectures deliver the same classification results, is that normal?

I have a data set with 600 data points with about 10 attributes (binary). The dataset has been normalized: Xnormalized = StandardScaler().fit_transform(X) The ...
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1answer
64 views

How to transform specific type feature to yield better prediction?

I have a dataset with 5K records focused on binary classification problem. I have about 60 features. Out of 60 features, around 45-46 features are of 'Min' and 'Max' type. For example, minimum blood ...
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9 views

Jupyter notebook memory consumption while training vs script

Anyone seeing this issue where, when you're training a model with torch on Jupyter Notebook your GPU memory utilization is more than if it was a python script? Ran the same notebook through a script ...
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1answer
54 views

How to Maximize recall for Minority class?

I have a dataset with 4.7k records and 60 features. 1558 records of indication label 1 and 3554 records indicating label 0. Am ...
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0answers
25 views

How to load the .h5 file and do transfer learning using fastai?

I have the pre-trained model in .h5 format, how do I load it and do transfer learning using fastai? I am currently using Keras to do transfer learning, but Keras doesn't have certain functionalities ...
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15 views

Validation score during training and checkpoint is different in keras

I have a tabular data with about 1500 columns where every column except the 1st column is sparse. I am trying to train a Feedforward neural network (1 hidden layer with 32 neurons) for a binary ...
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0answers
25 views

Incentivizing curiosity in a sparse reward environment

I'm quite new to reinforcement learning, but have been exploring different kinds of architectures (DQN, dueling DQN, actor critic, etc.) and evaluating their ability to solve certain problems. The ...