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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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32 views

Threshold to consider new feature as a new finding to a model?

I am working on binary classification problem with 5K records and 60 features. Through feature selection, I narrowed it down to 14 features. In existing literature, I see that there are well-known 5 ...
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27 views

How neural style transfer work in pytorch?

I am using this pytorch script to learn and understand neural style transfer. I understood most part of the code but having some hard time understanding some parts of the code. In ...
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25 views

How to build a OCR for reading text from image?

This is my first time working on a OCR application. I have lot of scanned images of English text-book pages like this and I want to build a OCR using DL to ...
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1answer
36 views

ML Project - Achieve 2 Objectives

I have a dataset with 5K records focused on binary classification. I am posting it here to seek your suggestions on project methodology Currently what is my objective is 1) Run statsmodel logistic ...
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1answer
15 views

Pretraining a neural network to teach it general information

Let's say that I want to train a neural network to recognize symptoms of severe dehydration in distance runners visually. Runners tend to finish races either overhydrated (hyponatremic) or dehydrated, ...
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19 views

How we compare two paragraphs of unlabelled dataset semantically (STS)?

Column representation: Unique_id | Text1 | Text2 Unique_id 0 Text1 public show for reynolds suspension of his coaching licence. portrait sir joshua reynolds portrait of omai will get a public airing ...
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28 views

Building a deep learning model to predict 2d arrays

Lets assume we have a 2D Testdata Array (arr1, 5k entries, values 0 to 1) like ...
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1answer
26 views

How to train Ner Model having 1 entity?

I am Creating a Custom NER (named entity recognition ) Model using bi directional LSTM and CRF. During Study on Ner i see all example includes Multiple entities per sentence. For eample this ...
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2answers
32 views

Which metric to choose for tracking model performance?

I am working on a binary classification problem with class proportion of 33:67. Currently what I am doing is running multiple models like LR,...
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2answers
34 views

How does L1 regularization make low-value features more zero than L2?

Below formulas, L1 and L2 regularization Many experts said that L1 regularization makes low-value features zero because of constant value. However, I think that L2 regularization could also make zero ...
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17 views

How to evaluate a content recommendation model unsupervised (unlabeled dataset)?

I have a lot of unlabeled data which is crawled from job listings and I'm trying to build a content based recommendation model. I just need if someone could help me out on how to evaluate such model. ...
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1answer
23 views

Facial recognition architecture

Image recognition uses deep learning, and in particular CNNs to train on and recognise faces. Usually, this entails training on lots of data. However, recently, we have seen face recognition being ...
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1answer
41 views

How to select best feature set and not ranking for tree based models?

I am currently using feature selection approaches like filter, wrapper, embedded etc. All these methods give different set of ...
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2answers
298 views

Auto ML vs Manual ML for a project

I recently was introduced to a AUTO ML library based on genetic programming called tpot. Thanks to @Noah Weber. I have few ...
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1answer
236 views

feature selection using genetic algorithm in Python?

I have a dataset of 4712 records and 60+ features working on a binary classification problem. I already tried out all the feature selection approaches like ...
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2answers
32 views

How can we perform STS(Semantic Textual Similarity) on UnSupervised dataset using Deep Learning?

How to implement STS(Semantic Textual Similarity) on unlabelled dataset. Dataset column contains Unique_id, text1(contains paragraph), text2(contains paragraph). Ex: Column representation: Unique_id ...
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1answer
14 views

Does it make sense to expand word embeddings so that each array index is a feature input or should the embedding itself be a model input?

If you are building a DNN, say, with two layers, and you want to use embeddings as one of your feature inputs, what's the best way to input the embedding? I'm trying to understand if I should break ...
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32 views

How to use arctan2 function inside Keras model?

I'm trying to add arctan2 function to the end of Keras model, but it looks like it is not getting any near even local minimum. Here is my ridiculous but minimal ...
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27 views

Dataset for musical Instruments recognition

I am looking for a "rich" Dataset to Teach my model to seperate Music intruments .. any Suggestion ? I found the URMP Dataset but it doesn't have many files.. I appreciate your help thanks and happy ...
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39 views

1: 10 rule in logistic regression - EPV

I have a dataset with 4712 records. Label Yes - 1558 records and Label No - 3554 records. I read online that ...
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2answers
54 views

How to perform bootstrap validation?

I am working on a binary classification problem. I ran cross-validation and grid-search on train data. Later I validated the model on my test data as shown below ...
2
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1answer
29 views

Why I get a very low accuracy with LSTM and pretrained word2vec?

I'm working on a reviews classification model with only two categories 0 (negative) and 1 (positive). I'm using pre-trained word2vec from google with LSTM. The problem is I get an accuracy of around ...
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54 views

Why a significant risk factor doesn't increase AUC-score/F1-metric?

I have a binary classification problem with 5K records and 60+ features/columns/variables. dataset is slighlt imbalanced with 33:67 class proportion What I did was 1st) Run a logistic regression (...
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28 views

Why do BERT classification do worse with longer sequence length?

I've been experimenting using transformer networks like BERT for some simple classification tasks. My tasks are binary assignment, the datasets are relatively balanced, and the corpus are abstracts ...
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54 views

ValueError: Graph disconnected: cannot obtain value for tensor Tensor

I'm trying to perform a stacking ensemble of three VGG-16 models, all custom-trained on my personal dataset and having the same input shape. This is the code: ...
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1answer
50 views

Val_accuracy (val_acc) very low

We have a data set that is converted from signal data to video. We want to classify these images using convolution. We tried many different methods but val acc is consistently low. Training accuracy ...
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2answers
101 views

Deep Q Network gives same Q values and doesn't improve

I'm trying to build a deep Q network to play snake. I've run into an issue where the agent doesn't learn and its performance at the end of the training cycle is to repeatedly kill itself. After a bit ...
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1answer
29 views

How to interpret statsmodel output - logit?

I ran a logit model using statsmodel api available in Python. I have few questions on how to make sense of these 1) What's the difference between ...
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2answers
17 views

User profiling based on multiple posts

I currently have collected a dataset of different social media posts for each user with labels assigned to each user. I tried to use LSTM, and BERT for the text classification problem, So for each ...
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27 views

Tiny Video Network

According to this: ...
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8 views

What is rotation rectangle matrix in kitti dataset calibration file

I try to understand kitti calibration file in the file there is line contains something called rotation rectangle I guess it is a matrix, what does the matrix used for ? R0_rect: 9.999239000000e-...
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1answer
21 views

GAN loss function [closed]

I am new to deep learning field and I want to synthesize as accurate as it can be, can someone tell me how to construct loss function for such model, any answer will be a great help please do not ...
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1answer
49 views

difference between feature interactions and confounding variables

Let me define the problem space. I am working a binary classification problem. I am trying to build a causal model as well as predictive model. My aim is to find list of significant features (based ...
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1answer
121 views

How to interpret dummy variable in ML prediction?

I am working on a binary classification problem where I have a mix of continuous and categorical variables. Categorical variables were created by me using ...
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1answer
45 views

How should I approach such classification problem where the input is an array of integers?

I am training a model for predicting a number between 0 to 10 in this case. These are the number of roots of a polynomial. The input array for the number of polynomials is the coefficients of that ...
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2answers
80 views

How to adjust cofounders in Logistic regression?

I have a binary classification problem where I apply logistic regression. I have a set of features that are found significant. But I understand that Logistic regression doesn't consider feature ...
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0answers
19 views

Why is convnet transfer learning taking so long?

I am using transfer learning to train a binary image classification model using keras' pretrained VGG16 model. The code can be found below : ...
2
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1answer
26 views

How to justify a predictor in influencing the outcome?

I am working on a prediction (binary classification) problem Currently I get an AUC score of 85-86 and F1-score of ...
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1answer
45 views

How to interpret shapley force plot for feature importance?

I am trying to practice and learn shapley value approach to explain my predictions on a binary classification problem. However am having difficulty in understanding the below plot. 1) Does it ...
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10 views

GIven some similar pictures,how to detect and mark the differences among these picture by deep learning

Now i have certain images ,they can be classfied into tow groups :right and false .However, two sorts just have small differnece in the detail . (for example ,I possess two maps. Their content is ...
3
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1answer
64 views

ASR on low dataset

I am doing an ASR(automatic speech recognition) as master thesis on low key dataset. Voice and text data is labelled. There are around 4000 phrases and around 5 hours speech. I don't have background ...
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1answer
53 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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14 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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247 views
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15 views

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 ...
2
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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 ...
2
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2answers
33 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 ...