All Questions
36,119
questions
1
vote
1
answer
187
views
Dealing with missing data in SVD
I am a newbie to machine learning and I am trying to apply the SVD on the movielens dataset for movie recommendation. I have a movie-user matrix where the row is the user id, the column is the movie ...
CommunityBot
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0
votes
1
answer
459
views
LSTM - How to prepare train from a dataset which contains multiple observations for different events
I m using LSTM in a project related to MobiFall dataset which contains falls and daily activitives - such as walking, sitting etc - sensed by accelerometer, gyroscope and orientation sensors in x,y,z ...
CommunityBot
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1
vote
3
answers
2k
views
How to give a 3D Tensor as input to LSTM
I'm having X_train of shape (1400, 64, 35) and y_train of shape (1400,). I want to give X_train as input to LSTM layer and also ...
1
vote
1
answer
744
views
Training Word2Vec with names instead of sentences
I have scientific database with articles and coauthors.
using this database I am training word2vec model on co-authors.
Use use case here is to disambiguate authors.
I was wondering my approach here ...
CommunityBot
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0
votes
0
answers
5
views
Implementing padding and masking sequences for RNN
As an exercise, I'm building a network for binary classification of sequences (whether a sequence belongs to type A or type B). The network consists of an RNN with one LSTM layer, and on top of it an ...
- 103
-1
votes
0
answers
10
views
ValueError: in python
How to solve this Error?---ValueError: Invalid classes inferred from unique values of y. Expected: [ 0 1 2 3 4 5 6 7 8 9 10 11 12 13], got ['Afghanistan' '...
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2
votes
1
answer
820
views
How to handle a feature vector that could be variable length?
I would like to train a machine learning model with several features as input as X[] and with one output as Y. For example Every sample has a Data frame like this: ...
CommunityBot
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0
votes
1
answer
16
views
Text segmentation problem
I am new to ML and trying to solve problem of text segmentation.
I have a transcript of news show and I want to split this transcript into parts by topic. I tried to google and asked chatgpt and found ...
- 20.5k
3
votes
2
answers
401
views
What can we learn from PCA on non linear data?
Suppose we have dataset with 10 features which are not linear:
...
CommunityBot
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13
votes
1
answer
40k
views
How to make my Neural Netwok run on GPU instead of CPU
I have installed Anaconda3 and have installed latest versions of Keras and Tensorflow.
Running this command :
...
- 14.5k
2
votes
1
answer
709
views
How can I count the number of matching zero elements between two numpy arrays?
I have a function that returns the predicted accuracy of a time-series model. I have two equally-sized numpy arrays, one for the actual direction and one for the predicted direction. I'm classifying ...
- 14.5k
3
votes
1
answer
7k
views
Will Keras fit( ) function automatically shuffles the input dataset by default?
I am asking this model fit( ) function.
fit(x=array_x, y=array_y, batch_size=32, epochs=10)
The question is straightforward:
Whether fit( ) will automatically ...
- 14.5k
13
votes
1
answer
5k
views
Stratify on regression
I have worked in classification problems, and stratified cross-validation is one of the most useful and simple techniques I've found. In that case, what it means is to build a training and validation ...
- 14.5k
13
votes
2
answers
24k
views
Activation function between LSTM layers
I'm aware the LSTM cell uses both sigmoid and tanh activation functions internally, however when creating a stacked LSTM architecture does it make sense to pass their outputs through an activation ...
- 14.5k
2
votes
1
answer
432
views
Image similarity: Similarity of mixed vector
In order to identify the similarity between images (products) I want to use a neural network approach similar to TiefVision. This pre-trained neural network is basically translating the images into a ...
CommunityBot
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0
votes
1
answer
17
views
RNN with PyTorch - I don't understand the initial parameters
I would like to understand the pyTorch RNN module in detail. There I created a very simple and basic example:
...
- 535
0
votes
2
answers
27
views
How to predicting the next date with Python ML
I have a list of dates around 10 dates in asc order. These are the dates a buidling was open. I need to predict the next date using this. I tried scikit learn like below
...
- 535
2
votes
1
answer
4k
views
Predicting next number in a sequence - data analysis
I am a machine learning newbie and I am working on a project where I'm given a sequence of integers all of which are in the range 0 to 70. My goal is to predict the next integer in the sequence given ...
CommunityBot
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0
votes
0
answers
7
views
Blip2 for image metada
I want to detect attributes of objects in an image - like what is color of a patch on shirt of person, how many patches are there, type of objects, exact dimensions of the objects etc
Heard of Blip2 ...
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1
vote
1
answer
27
views
How to find a vector representation for each descriptor?
Cubes data is well known data for extreme classification. Each picture has a set of descriptor along with it. Total data set has 312 descriptor. You will find list of descriptior in this file.
My ...
- 535
0
votes
0
answers
5
views
Interpretation of best subset selection regression model for factor variables with more than 2 levels
I applied the best subset selection regression model in R from leaps package to my dat dataframe. ...
- 113
1
vote
1
answer
71
views
Brute-force feature selection and cross-validation
There is an existing score made of 10 parameters; each parameter is equally weighted & the total score is found by summing the score for each parameter.
I want to try to reduce the number of ...
CommunityBot
- 1
0
votes
0
answers
12
views
Analyzing the Suitability of Conda for Academic Deep Learning Projects
I am a PhD student in data science, basically I design a model for a Vision / Language task. The dataset and the state of the arts models are public. It has been 2 years that I trained myself to use ...
2
votes
2
answers
195
views
Modeling the influence of events order on probability
The case is to model if the sequence of events influences the probability of binary target variable. We have for example five different events which occur in time (event: A,B,C,D,E). They can occur in ...
CommunityBot
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1
vote
2
answers
41
views
Open source NLP annotation tool/library supports active learning
I am looking for an NLP annotation tool/library that supports active learning. I am looking for something that works in this scenario:
Annotating N samples.
Training a model on the annotated data.
...
0
votes
1
answer
381
views
Mask R-CNN Background Subtraction Implementation
I am currently attempting to reimplement a paper on fall detection (https://ieeexplore.ieee.org/abstract/document/9186597). It requires a background subtraction algorithm called Mask R-CNN. Are there ...
CommunityBot
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0
votes
0
answers
18
views
How to implement a custom loss function acting differently on multiple instances with keras?
I want to reproduce the results in "Online Neural Networks for Change-Point Detection" Hushchyn et al., but I'm having trouble implementing their loss function with Keras. The algorithm ...
0
votes
1
answer
303
views
need an explanation of the For Loop in the DBSCAN algorithm Demo
In the following code of the DBSCAN algorithm, as a beginner I need an explanation for what happens to the data in the bottom for loop and why ?
Generate sample data
...
CommunityBot
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0
votes
1
answer
11
views
Fit multiple models e.g classifiers -> stacking -> calibration without data-leak or getting too many datasets
I have some data X on which I want to do the following:
Train two models; SVM and Logistic Regression
Use a stacking classifier based on the models from (1)
...
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0
votes
1
answer
557
views
Dynamic Images in Tableau
A Tableau Workbook I'm working on has different users logging in to see the data for their company. In the dashboard I have created a dynamic image that shows the customer logo depending on who is ...
CommunityBot
- 1
1
vote
1
answer
152
views
What can help decrease outliers' influence on non-tree models?
I have a feature with all the values between 0 and 1 except few outliers larger than 1. I am trying to collect all the methods that can help to decrease outliers' influence on non-tree models:
...
CommunityBot
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1
vote
2
answers
176
views
Strange Behavior for trying to Predict Tennis Millionaires with Keras (Validation Accuracy)
I'm trying to make an NN with Keras to predict the ATP players that will get more than US$1 million in prize money based on their weight and height (from a dataset I mined some weeks ago), but I have ...
CommunityBot
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1
vote
1
answer
478
views
Sampling methods for Text datasets (NLP)
I am working on two text datasets, one is having 68k text samples and other is having 100k text samples. I have encoded the text datasets into bert embedding.
...
CommunityBot
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0
votes
1
answer
381
views
Help with easyocr fine tuned model inference
I have trained a custom model, I have the yaml file and pth file and the py file in the correct directories. But now I face this error
...
CommunityBot
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5
votes
1
answer
15k
views
Plot of ACF & PACF
There are 96 observations of energy consumption per day from 01/05/2016 - 31/05/2017. I am trying an ARIMA model in R to be fitted to these time series observations. I have chosen the frequency of ...
CommunityBot
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0
votes
1
answer
83
views
Does adding of many FC layers during re-training increase the model size ? Are there any ways to optimize the size of model?
I am re-training a pretrained model VGG16.
In the last layers, im using two FC layers of size 2048 each, with dropout=0.5.
When I saved the model, the size of the ...
CommunityBot
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0
votes
1
answer
249
views
Performing 1D Depthwise conv using Keras 2D Depthwise conv
I would like to perform a 1D Depthwise convolution (ie the first step of the depthwise-separable convolution) for a machine learning model I am working on. This means that for an input activation ...
CommunityBot
- 1
5
votes
2
answers
3k
views
Multidimensional scaling producing different results for different seeds
I took the data from here and wanted to play around with multidimensional scaling with this data. The data looks like this:
In particular, I want to plot the cities in a 2D space, and see how much it ...
CommunityBot
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0
votes
1
answer
74
views
How to deal with one output for multiple inputs?
Hei!
I want to train a model, that predicts the sentiment of news headlines. I've got multiple unordered news headlines per day, but one sentiment score.
What is a convenient solution to overcome the ...
CommunityBot
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1
vote
1
answer
832
views
faster alternatives to sparse.model.matrix?
I have a large dataset that is entirely categorical. I'm trying to train with it using xgboost, so I must first convert this categorical data to numerical. So far I've been using sparse.model.matrix() ...
CommunityBot
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-2
votes
0
answers
27
views
how do to divide the datasets into 80/20 per cent of training and test sets and 10 foldcross-validation during model training to minimize bias [closed]
for perfoming 10-fold cross-validation during model training to minimize bias.
I have used below attempt
from sklearn import model_selection
X_train, X_test, y_train, y_test = model_selection....
1
vote
1
answer
82
views
An Unsupervised learning method suitable for large categorical data sets
I want to detect anomalies in the bank data set in an unsupervised learning method. However, in the bank data set, all columns except time and amount were categorical data, and about half of them had ...
CommunityBot
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1
vote
1
answer
326
views
Predicting sparse time series data
I have a dataset of a couple of EV charging stations (10 min frequency) over 1 year. This data consists of lots of 0s, since there is no continuous flow of cars coming to charge, but rather ...
CommunityBot
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0
votes
2
answers
157
views
Can we use decreasing step size to replace mini-batch in SGD?
As far as I know, mini-batch can be used to reduce the variance of the gradient, but I am also considering if we can achieve the same result if we use the decreasing step size and only single sample ...
CommunityBot
- 1
1
vote
1
answer
762
views
Error on custom RNN/LSTM with multiple inputs
I want to implement a custom RNN/LSTM model similar to this. The model should take two separate vectors as input and process them. I was following keras tutorial to implement a custom keras layer and ...
CommunityBot
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0
votes
1
answer
31
views
Is this a case of leakage or not?
I have a set of data on individuals' performance in 1960,1970,1980 and 1990, e.g. chess rating in those years for a bunch of players with 40-year careers. I've been asked to build a model to predict ...
- 548
0
votes
0
answers
8
views
Problem with 2 variable PCA loadings- Loadings are the same for all variables
I'm working on a problem for which i want to do some dimensionality reduction using 3 different PCAs of 2 variables each. Basically i want to perform a PCA and keep the first component between the ...
0
votes
0
answers
9
views
I'm looking for a dataset on enviroment monitoring
I'm looking for a dataset related to environmental monitoring, made up of values obtained from various types of sensors (such as temperature, pressure, CO2...etc) for the purpose of a classification ...
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3
votes
2
answers
1k
views
Perceptron - Which step function to choose
I'm studying Perceptron algorithm. Some books use this step function
1 if x>=0 else -1
where x is a dot product between the weights w and a sample x.
Other ...
CommunityBot
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2
votes
1
answer
75
views
What kind of images/objects are the most easy for neural networks to detect?
I need to design a marker image that should be detected by the neural network. I am aware that it is not a complex task just to detect an image and this can be done with OpenCV alone. However the ...
CommunityBot
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