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20 views

Bounding box regression without a classification task

I am using PyTorch to create a model that detects certain objects in an image. I framed my problem as a regression on bounding boxes, without any classification task whatsoever. The reasoning behind ...
0 votes
0 answers
6 views

Multistep horizon strategies vs Seq2Seq

In the context of recurrent neural networks for forecasting, what is the relation between multi-step horizon strategies and RNN-based seq2seq? For example, is the following Multiple Output Strategy [1,...
  • 119
-2 votes
0 answers
11 views

What are the different types of data science [closed]

We want the different types of data science and it's technology and advantages
0 votes
1 answer
23 views

How to do an incremental update for the mean and standard deviation of tensor data?

I have a big dataset (some 400Gb) consisting of tensor data (shape is $(600, 600, 10)$) and I want to normalize this dataset before feeding it to a neural network but this dataset can't fit in my ...
0 votes
0 answers
13 views

why when I find the best accuracy for logistic regression then it give me this error (AttributeError: split not found)

after run this code I face the split not found error. ...
1 vote
1 answer
25 views

clustering time series with different sized time series

I have read this article on towardsdatascience and they teach how to cluster time series using the DTW distance and the TimeSeriesKMeans from the tslearn.clustering library. I also read the official ...
  • 13
0 votes
0 answers
4 views

What does bare asterisk in seaborn function call signatures mean? [closed]

The API reference for seaborn.kdeplot explains the function call signature as: ...
0 votes
1 answer
16 views

Animal population dataset

Does anyone know where I can find animal population censuses or datasets with different types of animals? It's for a paper on a type of sampling called capture-recapture sampling. Thanks.
  • 1
0 votes
0 answers
7 views

What is the relationship between HOG (Histogram Of oriented spat. Grad) and HOF (Histogram Of optical Flow)?

What is the difference between those two descriptors and what is their relation? I'm asking because most of the time when I stumble into the one I also stumble into the other, it feels like they're ...
1 vote
1 answer
27 views
+50

Clustering by using Locality sensitive hashing *after* Random projection

It is well known that Random Projection (RP) is tightly linked to Locality Sensitive Hashing (LSH). My goal is to cluster a large number of points lying in a d-dimensional Euclidean space, where $d$ ...
0 votes
1 answer
36 views

How do transformers differ from feature selection and regular machine learning?

This is perhaps a simplistic way of thinking, but to me transformers (attention based neural networks) focus on a subset of the input, learning what is important for the problem/prediction as the ...
  • 71
1 vote
0 answers
23 views

Personalized Recommendations In Content Based Recommendation System

I'm trying to create a content based recommender system. The system accuracy is quite enough when finding similar items but it's not as good as when recommending items to a specific user. I use ...
1 vote
0 answers
10 views

Filter relevant geojson data based on a selected datapoint

I'll outline the situation and challenge I have a bit more clearly. I have multiple different datasets: A set of locations where products are sold (name, long, lat) A geojson dataset with geometry (...
1 vote
1 answer
19 views

Which loss function to use for a convolution NN for noise removal of high resolution images

My task is to remove small random spots from my 4 mega pixel images. My strategy was to feed a convolution network these images as I have the true images without the spots in them. The current loss ...
  • 11
2 votes
2 answers
94 views

Stacking: Use predictions of train or test to create features for level 1 classifier

The question is pretty simple. In stacking, the predictions of level 0 models are being used as features to train a level 1 model. However, the predictions of what data? Intuitively it makes more ...
  • 143
0 votes
0 answers
18 views

Colab TPU restarting due to protobuf incompatibility

I am trying to train a TemporalFusionTransformer model from pytorch-forecasting on the free ...
  • 11
0 votes
1 answer
34 views

Visualize time series data

I have a time series data set with 3 parameters and 5 dates per time point which I would like to visualize. The problem is that the date time points (year) are not equal over the parameters: ...
  • 113
0 votes
0 answers
12 views

What kind of models are suitable for predicting a proportional dependent variable (apart from logistic regression)?

I have a task of building two ML models in Python to predict a proportional value. I have a small data set of a fitness club's classes where each row was a class held this year. I have to predict the ...
0 votes
0 answers
14 views

Movement Analysis (Unsupervised Learning)

I have some data on the movement of a drone, D piloted by multiple people, P. Multiple metrics on the its motion is recorded, example speed, acceleration, elevation, angles which will be denoted by X1,...
  • 13
0 votes
0 answers
14 views

Question about LSTM input

I am trying to use LSTM to predict user input but my question is how can you get the actual input of the user and let the LSTM predict it? I tried to check online but I dont see anything about it. I ...
1 vote
1 answer
40 views

Bertopic with embedding: unable to use find_topic

I've used BERTopic with success for the following tasks: get topics, visualise (topics, barcharts, documents ...) and DTM (extended to get area plot with considerable success). However, I am unable to ...
0 votes
0 answers
26 views

What is the Bayesian distribution of two p.d.f's?

I whant to make this: Theese are the inputs I'm traying to replicate this for my app, but don't know how its done. As you can see, there must be a preset value for the sigma with the inputs of type ...
0 votes
0 answers
10 views

Why does the permutation symmetry breaking in dropout have a regularizing effect?

I usually include dropout in the dense layers I include in neural networks. I've taken it as conventional wisdom that this is a regularization. I've also compared model test performance on the same ...
  • 162
0 votes
1 answer
19 views

Impact of many zeros in LightGBM Regressor training set

I have a LightGBM Regressor model with 15 features. 5 of these features have 98.7% NA for the training set. All five of the features are NA for each row. I impute the missing values with zero before I ...
  • 1
0 votes
0 answers
5 views

Best method for predicting percent usage based on time?

My organization implements wellness programs at other companies and we supply monthly reports on the percent of employees that use the program, as well as a prediction for what percentage will have ...
0 votes
0 answers
8 views

The val_accuracy is higher than training accuracy, and the test accuracy is very low compared to both val_accuracy and train_accuracy

I am training a CNN model where, Training data=687 , validation data=102 , testing data=79 The validation accuracy is higher than training accuracy The test accuracy is very low compared to both ...
0 votes
0 answers
13 views

knowledge graph embeddings using GNN vs. shallow embeddings

I want to encode a knowledge graph, but I'm unclear on the difference between using shallow encodings (TransE, RotatE, etc.) vs a GNN such as a GraphSAGE. It seems like the GNN approach would also ...
  • 1
0 votes
0 answers
27 views

Is it necessary to have a perfect correlation when using linear regression?

I am working on predicting BMI against weight, using linear regression. The scatter plot of the data can be found below. As you can see in the plot, there seems to be low (or no) correlation between ...
0 votes
1 answer
28 views

Is there a way I can double the punishment when model mis-classing to a specific class?

As the title I asked. For example: a model that predicts the probability of a stock price rising/falling. Let's say this is a triple-classification problem. If it predicts "RISING", while ...
  • 101
2 votes
2 answers
35 views

Finding useful noun 2-grams?

Q: How can I find noun 2-grams in the English language (e.g., "roller coaster", "test tube")? Better yet, how can I find them with proportions? Ultimate goal: Generate distinct ...
  • 121
0 votes
1 answer
49 views

One word changes everything NLP

I have a classification model (BERT) that classifies sentences as either question or normal sentences. But whenever a sentence has "how" word, the model chooses "question" class. ...
  • 89
0 votes
0 answers
15 views

Is it possible to "link-couple-connect" certain inputs with outputs in a MIMO seq2seq LSTM model?

I have a seq2seq model with encoder and decoder as LSTMs which takes INPUT as the past 4 days of building data (weather data, 5 zones data like occupancy, internal loads, indoor air temperatures, and ...
2 votes
1 answer
29 views

Question about non linearity of activation function

I have a basic question about activation functions. It is told that they are added to the network to introduce non linearity. However, the neural network itself is non linear. Isn' it? If we see any ...
0 votes
0 answers
19 views

read_csv, non-printing ascii delimiters, and multi index

I have some text data which uses the ASCII data characters 0x1e "group separator" and 0x1d "record separator"...
  • 101
0 votes
1 answer
23 views

How to generate structured parameters from a spectrogram?

Say I have an algorithm that accepts as input structured parameters of the following format, generates an audio clip and then a 512x512 spectrogram out of it: ...
  • 101
1 vote
1 answer
26 views

Naive Bayes implementation using SkLearn documentation

I am studying Naive Bayes classification method from Data Mining Concept and Technique by Han, Kamber, Pei. There is an example of how to find out the class probability using Naive Bayes classifier. ...
  • 309
-1 votes
1 answer
32 views

Sklearn vs Pytorch vs Tensorflow vs Keras

I just need to understand the differences between sklearn, pytorch, tensorflow and keras in terms which implements traditional machine learning algorithms ( Linear regression , knn, decision trees, ...
0 votes
0 answers
34 views

High diversity between val_accuracy and evaluation results

I'm working on a multiclass text classification problem. After splitting the data to train and validation data frames, I've performed text augmentation to balance the data (only on the train data of ...
  • 135
-2 votes
0 answers
21 views

Is tree.DecisionTreeClassifier in python choosing the best classifier? [closed]

I was looking at this tutorial. http://www.cse.msu.edu/~ptan/dmbook/tutorials/tutorial6/tutorial6.html ...
  • 9
0 votes
0 answers
14 views

Strange results using UNet for image restoration

I am trying to use U-net type network structure on image restoration type task. However my results have strange color with check board artifact (As shown in the third image). Any advice? This is my ...
-1 votes
0 answers
10 views

Twitter API Query Format Issue [closed]

I'm trying to leverage the Twitter API for some research with Jupyter Notebook. I've been using http://noteable.io/ which is just another online jupyter notebook solution as it's free. I'm using the ...
  • 1
0 votes
1 answer
24 views

SkLearn Categorical Naive Bayes Vs Mathematical theory of Naive Bayes

The Naive Bayes classification based on the following formula $P(C_i|X) = {P(X|C_i)P(C_i) \over P(X)} ... i)$ $P(X|C_i)$ is the posterior probability of $X$ conditioned on $C_i$, $P(X)$ prior ...
  • 309
0 votes
1 answer
18 views

How does one perform a Canova-Hansen test in Python?

I am referring to the documentation here, but it does not give many examples on how to actually perform the test. I have a pandas dataframe with two columns: Column 1 is first day of every week, ...
  • 5
0 votes
0 answers
10 views

How to calculate weekly percentage of total sum?

I'd like to Calculate weekly index per item with the formula " sum of total"/"sum of a week". The data table is connected to a date table with week numbers. So each item should ...
-1 votes
0 answers
14 views

Suggestion for visualization in deep learning

I am working on a basic Neural network and want to show performance of model with respect to different parameters. I need help with suggestions for impactful visualizations. I can not make ...
0 votes
0 answers
8 views

Overall acurracy +/- E (with 90% C.I.)

I am assessing the accuracy of my classification model. I performed a 4-folds cross-validation and I obtained the following OA = (0.910, 0.920, 0.880, 0.910). So, the average OA is 0.905. My dataset ...
  • 101
-1 votes
0 answers
12 views

How to setup a pipeline for online and batch processing

I am developing a classifier model in python which will be applied to streaming data. During the feature engineering and training phase I have access to a historical database. What is the best way to ...
-1 votes
0 answers
12 views

Counting the number of parameters in CNN

I could not find the answers of the following questions. Q.1. You have an input volume of 32 x 32 x 3. You want to process time-series data with a 1D CONV with zero padding, stride of 1, and 2 filters ...
0 votes
1 answer
40 views

Plotting a no-skill model in a precision-recall curve

I am following this tutorial to apply threshold tuning using precision-recall curve for an imbalanced dataset Within the tutorial, a no-skill model is defined as: A no-skill model is represented by a ...
  • 345
0 votes
0 answers
15 views

Proof that averaging weights is equal to averaging gradients (FedSGD vs FedAvg)

The first paper of Federated Learning "Communication-Efficient Learning of Deep Networks from Decentralized Data" presents FedSGD and FedAvg. In Federated Learning the learning task is ...

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