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Questions tagged [sequence]

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Classification when the classification of the previous itens matter

I have a classification problem to solve, that seems to be common but I am struggling to find the name of this task and the best way to model this problem. Suppose I have a series of events that are ...
bratao's user avatar
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3 votes
2 answers
3k views

Running out of memory when training Keras LSTM model for binary classification on image sequences

I'm trying to come up with a Keras model based on LSTM layers that would do binary classification on image sequences. The input data has the following shape: ...
Alex's user avatar
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3 votes
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304 views

Why embedding or rnn/lstm can not handle variable length sequence?

Pytorch embedding or lstm (I don't know about other dnn libraries) can not handle variable-length sequence by default. I am seeing various hacks to handle variable length. But my question is, why this ...
sovon's user avatar
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3 votes
0 answers
1k views

TypeError: unsupported operand type(s) for %: 'int' and 'NoneType'(Stateful LSTM Keras)

So I have a trained LSTM model with which I am trying to predict future values. The model is stateful as seen below ...
hisairnessag3's user avatar
3 votes
0 answers
191 views

Next events prediction based on previous events

I have data set of sequences of user executed commands sorted in the order of its occurrence. The data looks like this. ...
msp12's user avatar
  • 31
2 votes
0 answers
130 views

1D Sequence Classification

Cross-post from https://stackoverflow.com/questions/71752744/1d-sequence-classification I am working with a long sequence (~60 000 timesteps) classification task with continuous input domain. The ...
Kevin's user avatar
  • 163
2 votes
1 answer
28 views

How to use time-sequence data with "meta data" of single value per sample?

I'm, trying to estimate a fish weight by a time-sequence signal of the change in resistance when the fish goes through a gate with electrodes installed. When the fish pass through the gate there's a ...
Shay's user avatar
  • 23
2 votes
1 answer
45 views

Comapring hidden markov models

Given a set of sequence transitions, there are different orders of hidden markov models that can be fitted to a dataset. Is there any test to determine which is the best model for a given sequence ...
APaul31's user avatar
  • 21
2 votes
1 answer
210 views

What's an appropriate datastore for variable length sequence data for PyTorch consumption?

I have a large number of sequences - potentially hundreds of thousands - each consisting of between 100 and 10,000 items, which each consist of about 5 floats. I need a datastore that can rapidly ...
Sam's user avatar
  • 121
2 votes
0 answers
709 views

Proper loss function for sequence prediction model with multi-step output

Consider a typical time series (sequence) prediction problem that use previous $k$ step historical features to predict the next step target. We use RNN model as an ...
JunjieChen's user avatar
2 votes
1 answer
566 views

Sequence models word2vec

I am working a data-set with more than 100,000 records. This is how the data looks like: ...
stats_171990's user avatar
2 votes
0 answers
70 views

Mapping “event” series, with segments of variable length, to time series for loss calculation

I have a time series of data which I map to a time series of non-exclusive binary features (in my case, short-time audio spectrograms to features of the audio). I will refer to a collection of these ...
Anaphory's user avatar
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2 votes
0 answers
85 views

Classifying sequences of mouse clicks with different number of clicks per sequence

I have a series of sequences, each sequence contains multiple mouse click with the following features: [x coordinate on screen, y coordinate on screen, duration of click], and each sequence is labeled ...
Andrej Naumovski's user avatar
2 votes
0 answers
501 views

k- means clustering on Markov chain trasition probability

I have data set of 50 students. I want to cluster them on their sequential data ( While doing a job they followed multiple sequences A, B, c total 7 stages). I am planning to apply k-means clustering ...
Bloodstone Programmer's user avatar
2 votes
0 answers
84 views

Classifying Sequences Where Some Sequences in Both Classes

I am building a modified RNN (specifically a GRU) to classify sequences. These sequences are of variable length, and contain "states". Each point in the sequence is categorical and they look like [A,B,...
Carter's user avatar
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2 votes
2 answers
211 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 ...
Luc's user avatar
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1 vote
1 answer
103 views

Which should we choose: sequence-model vs n-gram model and why does it depend on ratio of Samples / Words per Sample

This ML tutorial from Google is analyzing the imdb reviews dataset to predict the tag positive or negative. When choosing a model Calculate the number of samples/number of words per sample ratio. If ...
Nate Anderson's user avatar
1 vote
0 answers
27 views

Techniques for early binary classification from sequences revealed over time in a low data environment?

We have data with objects, each of which has a series of events. A series is 1-50 events, revealed over time (a few months). These objects have events come in at different times during a season, so ...
dfrankow's user avatar
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1 vote
0 answers
55 views

Forecasting on multivariate time series containing quaternions

I have a multivariate time series containing 3D position data ($x,y,z)$ and orientation data (as quaternions) obtained from motion sensors. My goal is to forecast the future position/orientation, and ...
chronosynclastic's user avatar
1 vote
1 answer
14 views

What is the formal category of problem described by identifying consecutive occurrences of attributes in records?

Apologies for the garbled title, I'd really need to know the answer to the question before I could phrase it properly... Let's imagine I've got a data set of football(soccer if you prefer) match ...
Recalcitrant Caprine's user avatar
1 vote
0 answers
38 views

How to predict data from sequence of sequences of variable size?

input data ...
Emil's user avatar
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1 vote
0 answers
89 views

How to compare different forecasting models over different time horizon?

Developed multiple Models with AR, ARIMA, VAR; LSTM , SARIMA. Now, the purpose is to find out which model performs best on a given use case with different time horizons. The time series data is ...
Mannheimer_Coder's user avatar
1 vote
0 answers
513 views

How does data shuffling work when LSTM is involved?

TIL that when using the LSTM layer, the states are remembered throughout the same batch. When using stateful LSTM, they can be even remembered outside of the batch. The first realization gave me a ...
JohnnyQ's user avatar
  • 201
1 vote
0 answers
44 views

Text generation with deep neural network?

For my master's project, I have to build a deep learning model for text generation: the model learns on a set of sentences, then it generates new sentences based on those from which it learned. I ...
zakya's user avatar
  • 11
1 vote
1 answer
223 views

Handle with very short and very long sequences with Neural Network

I am working on multi-class problem with sequences. My dataset is composed of sequences of data with different length. E.g. 1500 labeled samples: 500 datapoint belongs to class A, 500 class B and 500 ...
scalessio's user avatar
1 vote
1 answer
44 views

How can I predict the last element of the fixed length=8 sequence after I get each element?

There are fixed length lists [X1, X2, X3, X4, X5, X6, X7, X8] like this. I have many lists like them from the past. In the future, I will get new element of current list on weekly bases. one new ...
Roman Kutubidze's user avatar
1 vote
0 answers
112 views

Create sequence for a Conv1D layer

Im studying the following tutorial on the Keras website and I'm trying to understand how to create a sequence for a Conv1D layer. This is their method: ...
Fabio's user avatar
  • 53
1 vote
0 answers
127 views

Machine learning for circular sequences

My data are sequences of real numbers $a_0,a_1,...,a_{n-1}$. The length of a sequence is fixed and equals $n$. Each sequence is mapped to a real number $y$ and I want to predict $y$ given the sequence....
Vladislav Gladkikh's user avatar
1 vote
0 answers
19 views

What is External representation of time in Sequential learning?

I am reading the literature on sequential learning and it is often mention that in order to handle sequential/temporal data, there two categories of work in sequential learning External ...
A.B's user avatar
  • 336
1 vote
0 answers
39 views

Long sequence prediction with model trained on short sequence

I'll start with a specific example. I would like to train model which predict vector of [0-1]. Values close to 1 on specific range indicates that in those timesteps is particular activation word (...
xana's user avatar
  • 161
1 vote
0 answers
39 views

Time Series Forecasting with RNN/LSTM/NARX

I have some experimental datasets (like 4 or 5), and each dataset has three time series data, say $u1(t)$, $u2(t)$, and $x(t)$. The three time series of each experiment are similar but not the same. ...
Zihan Wu's user avatar
1 vote
0 answers
26 views

What is the problem classification (e.g. sequence-to-sequence) for prediction of an autocorrelated sequence from multiple autocorrelated sequences?

I will try to provide a simple example to illustrate my question. I have training data for many oil wells. The training data consists of the well identifier, a timestamp, other relevant properties ...
sawyer_bro's user avatar
1 vote
0 answers
51 views

Optimizing ad placement using historical data

Edit: increased generality. I have an ad placement optimization problem and I am brainstorming to determine which ML techniques are well suited to it. Basically, I have some objective that involves ...
Sledge's user avatar
  • 254
1 vote
0 answers
1k views

Code or Package to cluster sequences (or time series) of different lengths based on HMM?

Is there any existing code or packages in Python, R, Java, Matlab, or Scala that implements the sequence clustering algorithms in any of the following 2 papers? 1) 'Clustering Sequences with Hidden ...
mflowww's user avatar
  • 111
1 vote
0 answers
930 views

Sequence Embedding

Is there a way to get embedding for an ordered sequence of vectors? I want to get embeddings to feed them further into net i.e. train it to arbitrary loss function simultaneously for embeddings and ...
Darel's user avatar
  • 11
1 vote
0 answers
94 views

How do I separate Interleaved sentences using LSTM networks?

I have a problem statement wherein the following input The James world Bond shall can't end save us tomorrow. must be converted into this - The world shall end tomorrow & James Bond can't ...
Manish Narang's user avatar
1 vote
0 answers
658 views

RNN sequence length and cell size

I am trying to build a RNN model to classify time series. My time series data consist of numbers with length 200. I am using tensorflow, and when i create the placeholder for the data it is like this:...
Ploo's user avatar
  • 333
1 vote
1 answer
312 views

Clustering sequences of sentence embeddings

I have a sequence of events, right now I am not worried about their actual times, just the order. This is a sequence of web page views. I have modelled my data as the following, where each element ...
dendog's user avatar
  • 120
0 votes
0 answers
18 views

Calculating prediction confidence from a sequence of token-level confidences

I am working with OCSR (optical chemical structure recognition) models, and they output a sequence of token-level confidences. I am looking for a method of summarising these token-level confidences ...
finlay morrison's user avatar
0 votes
0 answers
30 views

Predict best chess move using RNNs

I am trying to do a project with AI: in which during any certain moment of a chess game i can predict, using a RNN trained on a kaggle dataset, the best possible move that i can make. I am having ...
user3253067's user avatar
0 votes
0 answers
9 views

Are the filtering problem and decoding problem the same thing?

Is there any distinction the filtering problem and the decoding problem? Wikipedia's definition for a filtering problem is: The problem of estimating the states or ideally the posterior distribution ...
Tommaso Bendinelli's user avatar
0 votes
0 answers
44 views

Improving Wake-Word Detection Model Performance: Seeking Advice and Suggestions

I was assigned a task to train a wake-word detection model. Basically, it's a binary sequence classification model on audio samples where it should be 1 if it recognizes the wake word being said (e.g. ...
Ícaro Lorran's user avatar
0 votes
0 answers
18 views

Conditional density estimation for sequences using conditional random fields

I am looking to estimate the conditional distribution of the next observation $x_{t+1} \in \mathbb{R}_+$ of a discrete-time process, given the current observation and $l$ previous observations. I am ...
Jonas's user avatar
  • 1
0 votes
0 answers
28 views

Why use sliding window input features in deep learning?

I was reading through the DNABERT paper and found that their input features were k-mers. This is equivalent to using rolling/sliding window features in the other common family of sequential problem, ...
Avatrin's user avatar
  • 131
0 votes
1 answer
49 views

Sequence prediction in Parent - Child dataset

We have a large collection of documents (D), each accompanied by a set of metadata (M). Within this collection, some documents act as parent documents and have multiple child documents. Both parent ...
6nagi9's user avatar
  • 101
0 votes
1 answer
50 views

Classification of sequential data

I'm currently trying to classify discrete sequential data into five classes with machine learning. The setup is the following: The actual object is filled with various properties, but to separate the ...
bitfish31's user avatar
0 votes
1 answer
40 views

Deep Learning Model to predict sum of Sequences based on flag value

I am trying to Predict Sum of the Sequence based on flag but my model is not able to converge. for each time stamp, include the first element in sum if second number is 1 in Sequence. Example ...
Anup Patel's user avatar
0 votes
0 answers
32 views

Time-Series analysis with small data set, but long sequences

I'm working on a time-series classification problem. There are 3 classes. Dataset consists of 6 sequences from each class (total 18 sequences). Each sequence is 19,000 in length. What are some time-...
siaabd001's user avatar
0 votes
0 answers
1k views

Timestamp sequence classification

I am trying to classify a series of timestamps using RNN with LSTM. The data consists of timing information extracted from the uplink packets recorded during a website fetch. The dataset contains 100 ...
Hryniu's user avatar
  • 1