Questions tagged [sequence]

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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
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1 answer
33 views

what's this approach to spatiotemporal data named as?

I have some sequential data (e.g. audio, video, text etc.) and I am using this approach to classify sequences. I am sure there's a name for it, but I can't think of it: ...
Santino's user avatar
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1 answer
318 views

Similar algorithm to apriori to find unpopular sequential patterns

I am working with a dataset that looks like similar to this one but it is way larger (approx. 30.000 arrays): ...
Eve Edomenko's user avatar
1 vote
1 answer
107 views

HMM and its competitive alternatives

In Natural language processing, what are the major applications of Hidden Markov Chain (HMM), and what are the alternatives that usually can outperform HMM, is RNN and LSTM always the choice right now?...
user288609's user avatar
4 votes
2 answers
955 views

Can bidirectional RNN use variable sequence length?

A bidirectional RNN consists of two RNNs, one for the forward and another for the backward sequential directions, which outcome is concatenated at each time step. Would this configuration restrict the ...
DiMorten - Jorge Chamorro's user avatar
1 vote
1 answer
49 views

How and When features are attached to target label

I am using Mallet CRF library and having training set sequences like below. ...
Kanagavelu Sugumar's user avatar
2 votes
1 answer
192 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
5 votes
2 answers
212 views

Predict a sequence given many sequences

I'm trying to find an algorithm that would fit this use case: My data: a bunch of fixed-size integer arrays, e.g. [0,2,3,4,5] [1,2,3,1,5] [4,1,2,4,5] ... Input: ...
Andrew Furman's user avatar
1 vote
0 answers
31 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
1 answer
47 views

Can OLS regression be used to predict from a complete sequence of data?

Reading online and following this example from scipy I understand OLS can be used to find data between gaps in a sequence (interpolate?) but I already have a complete sequence and want to predict the ...
developer1's user avatar
1 vote
1 answer
158 views

Sequence labeling with partially known labels

I am working on a sequence labeling task where, based on experience, many of the labels of a given input sequence can be reliably extracted with a simple rule-based approach. For example, considering ...
zepp133's user avatar
  • 111
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2 answers
51 views

Which input to use when generating a new sequence

I want to use sequence-to-sequence architecture to generate sequences. My data has such structure ...
Kenenbek Arzymatov's user avatar
1 vote
1 answer
287 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
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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
2 votes
1 answer
29 views

Use LSTM to predict the proportion of steps with nonzero feature values

I am trying to do a simple regression for sequences. Each input $X_i$ is a $n=2000$ by 1 matrix, formatted as $n_i$ 0-s followed by $(n-n_i)$ 1-s. The output $y_i$ should be $n_i/n$, i.e. the ...
physcis_beginner's user avatar
2 votes
0 answers
678 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
3 votes
1 answer
109 views

User actions sequence classification

I have a training set where each row is a series of user actions on a website (logged in, sent an invoice, etc.) and times deltas in ms between these actions. Each row has a label — a corresponding ...
Klimentij Bulygin's user avatar
2 votes
1 answer
241 views

Multiple merging multiple convolutions

(First post here) I am rather new to neural networks, having used Tensorflow for a couple months now, and am looking for some advice I have on an idea to improve the accuracy of my model. I am looking ...
superhelicase's user avatar
4 votes
1 answer
187 views

Best HMM Package

What is the best HMM (Hidden Markov Model) library available in Python? I have already looked into seqlearn and hmmlearn, but both of them don't seem to be actively maintained. Thanks in advance!
Edamame'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
  • 131
1 vote
2 answers
5k views

LSTM to multivariate sequence classification

How can I train multivariate to multiclass sequence using LSTM in keras? I have 50000 sequences, each in the length of 100 timepoints. At every time point, I have 3 features (So the width is 3). I ...
Cranjis's user avatar
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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
3 votes
0 answers
295 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
  • 521
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
2 votes
2 answers
86 views

Sequence prediction with unlimited predictions

I have a special kind of prediction problem. I have observed $M$ sequences $X_m = [x_1, x_2, ..., x_N]$ where the distance $d$ between $x_n$ and $x_{n+1}$ is drawn from the same normal distribution, ...
hwaxxer's user avatar
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1 vote
1 answer
206 views

Any non Deep Learning python packages for sequence classification.?

Stats model or any other machine learning python packages for doing sequence classification(that can be multi class) and sequence prediction (Both next step and regression). PS : Input data will be ...
IamTheRealFord's user avatar
12 votes
1 answer
13k views

what is the first input to the decoder in a transformer model?

The image is from url: Jay Alammar on transformers K_encdec and V_encdec are calculated in a matrix multiplication with the encoder outputs and sent to the encoder-decoder attention layer of each ...
mLstudent33's user avatar
0 votes
2 answers
62 views

Statistical methods for Sequence learning

I am bit more traditional and I am looking for a statistical method that can help me also do inference or predictions. I have some table that contains some transitions, where each row of the table ...
Alex P's user avatar
  • 41
2 votes
1 answer
2k views

bert-as-service maximum sequence length

I installed bert-as-service (bert-as-service github repo) and tried encoding some sentences in Japanese on the multi_cased_L-12_H-768_A-12 model. It seems to work ...
mLstudent33's user avatar
1 vote
0 answers
49 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
0 votes
1 answer
101 views

Classification of keystrokes

A year or two ago I wrote a keylogger that has been quietly running in the background of my computer. Each line consists of a timestamp, a keycode, and a value representing modifier keys (e.g. ctrl, ...
Jesse Aldridge's user avatar
1 vote
1 answer
4k views

Machine learning Classification model for binary input and output data

I have a large longitudinal dataset with 5 minute granularity for a period of around 30 months from thousands of households. I would like to classify them using a binary output (0/1) based on the ...
Kirti Sundar Sahu's user avatar
3 votes
2 answers
2k views

What clustering algorithm is appropriate for clustering paths?

I have a dataset with vectors in 2-dimensional space that form separate sequences (paths). Full data is presented below: , while a random sample of 5 paths looks like below (please note that ...
Kuba_'s user avatar
  • 264
2 votes
2 answers
7k views

What algorithms are good to predict next numbers?

Let's consider we have several hundreds of numbers like ( 1, 2, 5, 8, 7, 15, 19, 8, 4, 6, ...) those are closed numbers of a stock on consecutive days for example. I like to know what algorithms are ...
user3486308's user avatar
  • 1,260
4 votes
1 answer
2k views

Why do position embeddings work?

In the papers "Convolutional Sequence to Sequence Learning" and "Attention Is All You Need", positions embeddings are simply added to the input words embeddings to give the model a sense of the order ...
Robin's user avatar
  • 1,307
2 votes
2 answers
1k views

Give Variable Length input to LSTM

My input data consist of list of list. Both list have dynamic length for every example like below. ...
Batuhan B's user avatar
  • 226
1 vote
1 answer
71 views

What exactly does the model generation mean in this diagram?

I've been trying to grasp a research paper on image colorization using neural networks here I am stuck at this diagram. What I need help on, is the Model Generation step after Feature extraction. ...
Sachin Titus's user avatar
2 votes
1 answer
539 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
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
2 votes
1 answer
497 views

Neural network for variable length data classification

How can I create a network which can predict labels of variable lengths data: Training data: ...
rnso's user avatar
  • 1,558
2 votes
0 answers
68 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
  • 140
1 vote
0 answers
925 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
4 votes
2 answers
1k views

Is this a problem for a Seq2Seq model?

I'm struggling to find a tutorial/example which covers using an seq2seq model for sequential inputs other then text/translation. I have a multivariate dataset with n number of input variables each ...
Ellio's user avatar
  • 93
2 votes
1 answer
529 views

Query on unstable loss curves for RNN

I’m currently building sequence models for forecasting, and have tried using RNNs, LSTMs, and GRUs. Something unusual I noticed was the highly unstable loss curves, where the loss sometimes goes back ...
Eugene Yan's user avatar
3 votes
1 answer
293 views

LSTM training/prediction with no starting sequence

ML newbie here. As an exercise, I'm trying to build a character based language model based on a simple 1 layer LSTM. Based on what I've learned about LSTMs, a common usage is to take in a sequence of ...
Seth's user avatar
  • 181
2 votes
0 answers
83 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
4 votes
3 answers
563 views

Are there cyclic decision trees?

Usual decision trees are directed acyclic graphs. Are there generalizations of decision trees that contain cycles analogously to recurrent neural networks? If such trees exist, can they be applied to ...
Vladislav Gladkikh's user avatar
2 votes
1 answer
2k views

Very long sequence in neural networks

Beginner's question regarding sequences in neural networks: suppose I have classification problem that looks like: X = very long sequence of varying length. Y = class (assume for simplicity y=0/1). ...
Roger T's user avatar
  • 31
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
1 vote
2 answers
48 views

Group prediction

I have following sort of data coming every day: (0)(3,4,5)(6,9,1)(5,35,12,232) (1)(5,1,4)(6,2)(12,54,12,43)(8,23,65) (2)(6,7,2)(34,3) (3)(4323,23,12,4543) (4)(987,32,324,23,224,12,213,21)(1,2) (...
user50711's user avatar