Questions tagged [time-series]

Time series are data observed over time (either in continuous time or at discrete time periods).

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15 views

Strange behavior of CNN when forecasting time series

I have a time series containing 5 features. I tried to use LSTM to predict the next 112 periods in the series. However, I got very bad results. So I tried to use CNN. First, it did not work properly ...
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34 views

outliers in time series

I have a data set like the following where the rows are dates and the columns are values recorded by different sensors on those dates. Before working with the data for the purpose of predicting it, I ...
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Data leakage when setting class_weight to tackle imbalanced time series data?

I'm using a random forest classifier from sklearn to predict whether a stock's return for the next period is greater than a certain threshold (say -2%), so negative is 0 and positive is 1, a binary ...
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72 views

Different accuracy of random forest and neural net

I ran a set of time series data in a neural net model and random forest model. For neural net I normalised the data split it into test 20%, validation and training 80%. Keras library neural net was ...
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19 views

Forecasting with two separate periods of time

I have a sales forecasting problem where I only have three months of year 2018 ( Jan, fev, march) and three months of year 2019 (oct, nov,dec) and I have to forecast the sales for all the months of ...
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Appropriate visualization for this kind of data

Late edit: currently working through the FlameGraphs bibliography here. It looks like what I'm doing is similar to an icicle chart, but with passage of time on the x-axis. The author mentions ...
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1answer
369 views

Attention for time-series in neural networks

Neural networks in many domains (audio, video, image text/NLP) can achieve great results. In particular in NLP using a mechanism named attention (transformer, BERT) have achieved astonishing results - ...
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2answers
60 views

Predicting Multiple Values Values Using Time Series Forecasting

I want to illustrate my question with the following example: I have a wholesale company through which I sell 200 products: P1,P2,P3 .... P200 to a 1000 customers ...
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1answer
20 views

Should I concat multiple stock timeseries datasets into one?

I have several timeseries datasets of stock data, with fundamental indicators. I would like to build a model that selects stocks for buy and hold. I understand that to perform this task I have two ...
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23 views

Predicting invoice data of 12 month using only 1 month data

I have only 1 month of historical data of invoices can I predict next 12 month of data with good accuracy if it is possible then which model should I used for prediction? Thanks
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138 views

Why does the smallest LSTM I can make perform so well on this time series forecast?

So I've been playing with some different forecasting methods on a data set that I have done some more basic analyses for in the past. Without going into to much detail, it's population data over time ...
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Which time-serie model is good when using concatenate data?

I would like to make a model using sequence datasets. As I've searched that , many LSTM, RNN tutorials use long-sequential data such as weather in 1950-2020. However, my datasets are short sequential ...
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1answer
29 views

Is feature scaling at all needed for a feature set with a single feature?

I understand that feature scaling is required to bring features in different magnitudes on a common scale so the model is not biased towards features with higher magnitudes. But if there is only a ...
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Understanding the network structure of a multiple timeseries fusion model

Please don't mark this question as duplicated to Can I create a layer with multiple rnn cell ? [question about a paper] It has already been marked 2 times , I admit they do refer to a same paper, but ...
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34 views

How to score the health of a company? [closed]

i'm currently doing dual apprenticeships. My main mission is to represent the health of a company based on accounting records for multiple companies over multiple years. The part of an accounting ...
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1answer
17 views

Does auto.arima of the forecast package deal with seasonality and trend automatically

I'm reading some code involving auto.arima method from the forecast package in R. What I'm curious is whether there is a ...
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In classical kernel regression, is there a task which responds almost exclusively to a single kernel choice?

I'm curious if there is any well-known kernel regression/classification task which can only be "solved" using a specific choice of kernel?
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57 views

How to train an LSTM model with data that has multiple input rows per day but only one row of label/ground-truth (output) data per day

I am doing a sleep data science experiment and I need a model that outputs multiple columns sleep quality measurement values (that are decimal numbers) for each input. For training, I collected data ...
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28 views

Can I create a layer with multiple rnn cell ? [question about a paper]

I am trying to implement https://dl.acm.org/doi/pdf/10.1145/3269206.3271794 . Structure: As it said: In particular, we integrate the embedding vectors learned from each individual recurrent encoder ...
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multi items forecasting: issue with storing results

disclaimer: I am not 100% sure that this is the appropriate place to ask this question. Here is a little bit of context about the problem. I have a dataset containing about 1000 products timeseries (...
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16 views

Input variable that influences only trend

I need to predict cost for the next 4 weeks. Along with categorical variables (available for future as well), I have a numerical variable (a value from the day before prediction - I don't have future ...
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Model and CV setup for structural timeseries forecast

I wrote this question on cross-validated, but no replies were yet made, so I'm posting here as well since the topic may overlap a little bit. I have no problem with deleting one off one of the sites, ...
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Dimensionality Reduction for Function Fitting method using Kernels

I have a set of continuous noisy measurements $x_i \in R^n$ with $i=1,...,N$ for which I know the value range, i.e. $x_{min} \leq x_i \leq x_{max}$. Corresponding to the measurements, I have a set of ...
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Which network structure to use for multivariate time series data with unknown input and output size at each time step?

I have data that has is multivariate and can be thought of as many sentences of variable length. I'm trying to predict what the next sentence will be and it depends on multiple preceding sentences. I ...
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1answer
22 views

How to get different length output using keras?

I am working on a time-series kind of problem. I have (timesteps, features) and the length of output will be (timesteps,). All ...
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12 views

understanding the use of additive or multiplicative scale of timeseries?

In python, by using seasonal_decompose we find whether the given time-series is having multiplicative scale or additive scale data. But, what is the use of finding it. I haven't seen it's use in ...
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25 views

Alterable Similarity Join for Time Series

I'm currently trying to implement the MPdist (matrix profile distance) algorithm for time-series data, but I've developed a new distance metric that I'd like to use in place of the Euclidean metric. I'...
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Tracking time-series latency using conjugate priors

I need to do a project using Bayesian statistics for a class and I am trying to apply it to my work. I help manage a time series database with 40,000+ different time series that we collect. The time ...
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Understanding kernels

In below formula Took this picture from: https://www.cs.toronto.edu/~duvenaud/cookbook/ what is the difference between x and x_dash ? Can we use this kernel if x is univariate time series and the ...
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1answer
30 views

Mining timelines in a long text

I am trying to detect timeline of brands histories. For my specific case, I believe it is easy because data is already clustered. For each Wikipedia article I can spot sentences surrounding dates. ...
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171 views

Was this dataset analysed correctly? [closed]

There's a Twitter thread going around that claims there are signs of voter fraud due to anomalies in the election vote count data set. You can download the dataset here and find the script to generate ...
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1answer
16 views

How to sample with guaranteed minimum spacing?

I have a timeseries stored as a pandas.Series, and have computed the autocorrelation to be negiligable for 12 hours lag. Therefore, I want to test the approach of ...
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2answers
56 views

no decrease loss and val_loss

I try to train a neural network for time series. I use some data from Covid, mainly the goal is knowing 14 days of number of people at hospital to predict the number at J+1. I have use some early ...
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1answer
93 views

Negative R2_score Bad predictions for my Sales prediction problem using LightGBM

My project involves trying to predict the sales quantity for a specific item across a whole year. I've used the LightGBM package for making the predictions. The params I've set for it are as follows: <...
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Time period of time series

Is it possible to get time period of a time series. Is there any library in python that can do this. I am aware of FFT and ...
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How can I model the autocorrelation of objective variables under the situation where we can't observe any actual objective variable in the test phase

I'm trying to model the relationship between the declared value from a subject and stimulus. For example, modeling a relationship between the subject's happiness and strength of stimulus so that we ...
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107 views

Time series forecasting - Multiple Parallel Input and Multi-step Output

I have a time series with 5 variables, and I want to predict the behavior of these 5 variables 112 periods ahead. For this, I use a dataset with information on the 21504 periods before (18278 periods ...
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10 views

Error bars for soft-DTW (Dynamic Time Warping) Barycenters

I'm currently exploring time-series data and describe the average of the data using soft-DTW barycenter as described here. My next concern is if it is possible to create a confidence interval / ...
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188 views

How to create Window sequence for TFX timeseries

I am building a TFX pipeline for timeseries with a uci open-source data https://archive.ics.uci.edu/ml/datasets/Appliances+energy+prediction. As timeseries training and evaluation requires window ...
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Detecting pushups based on pose data

I've been playing with Google's MLKit, and decided to detect push ups. As a quick test, I took the position of the left shoulder, and plotted the Y Axis. Here's how a variety of trials look: Five ...
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19 views

Loss function for 1d segment estimation

My problem is as follows: I have a long segment [say, 100000 samples] as input. Regardless of the method, I need to output a partition of this segment into k sub ...
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45 views

Ideal framing of data from LSTM + adding static features

I'm dealing with a problem that I'll try to simplify here : You have a land where you can plant seeds and water them. On each day, you have the total area being watered and you have area that has just ...
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13 views

Risk analysis on the uptime of web applications (classification? survival analysis?)

I've conducted a couple studies examining how "risky" several web applications are based on whether the respective support teams raise a major incident ticket. The data we have includes the ...
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37 views

Drowsiness Detection issue understanding LSTM input shape

I’ve difficulty in understanding LSTM input shape. For example. I’ve 2 videos out of these 1 is categorized as Awake (0) and 1 as Drowsy (1). I preprocessed them to extract Eye Aspect Ratio and Mouth ...
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3answers
51 views

Time series classification, without the time dimension

Edit Thanks to the answer of @pcko1, I understand that I should use data augmentation to make my model resilient to order of data points. Clarification after the answer of @Icrmorin : My problem is ...
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2answers
86 views

how do I predict the next's alarms ? (time series) [closed]

I'm trying to solve a time series forecasting problem, where the main goal is to read data with various alarm logs and make a prediction about what may happen in the future. Specifically, my data is a ...
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1answer
201 views

Subsequence parttern matching for time series

I have a set of time series data (just like voice sequence data) with the pattern as shown in the first figure (theoratical data). The measured data is given as presented in the second figure. What I ...
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1answer
75 views

Questions about a multivariate timeseries forecasting model - keras

I have trouble understanding the model I'm trying to create. I have few questions so I'll explain my model first and what I'm trying to do: I have created sequences of data (input and ouput of the ...
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1answer
320 views

what is the complexity of a bidirectional recurrent neural network?

In particular, what is the complexity of a bi-directional recurrent neural network taking into account the variants of LSTM and GRU as well for training? I am hoping if I can get links to some ...
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59 views

Time series analysis model evaluation performance metrics integration in time series application

After study in time series analysis, I recognized RMSE and MAPE are the best evaluation metrics for used model in real time series application. But my queries are below as this is my first practice ...

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