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Questions tagged [time-series]

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

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Training multiple keras models and combining outputs to determine losses

I'm trying to predict the future states of a 1D travelling wave (square, triangle and sawtooth) using a deep learning setup in Keras. The waves are discretised in a 1024 data points. As this gives a ...
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LSTM : multi-step multidimensional multivariate multi-site timeseries forecasting

I'm working on a project in which i'm trying to do a pollution forecasting. I googled around and found that LSTM is a good candidate for this task, however, I'm still struggling at how to adapt it to ...
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Voting classifier using grid search for Time Series

I have three models Arima Auto ARIMA Double Exponential Smoothing I want to apply ensemble method - voting method and allow the classifier to learn weights for these three models. I have checked ...
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Time Series Prediction for non-uniformly varying dependent variables

I have a dataset with the following properties: DATETIME: range from "01.01.2014 01:00:00" to "12.31.2016 23:00:00" (index) Units: Category (#53) Technology: Category (#5) Capacity: Continuous value ...
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How to get the formulas used by seasonal_decompose for Trend and Seasonality

I'm trying to use decomposition to forecast into the future. From my reading I understand that I can do this by adding a trend formula to a seasonality formula. I know that I can decompose a time ...
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33 views

How to optimally train deep learning model using output as new input

I'm trying to train a network to predict the future. My current setup uses 5 time steps as inputs from the past, each consisting of 10 features, resulting in a [5, 10] input matrix (initially ...
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What is the largest public wearable accelerometer dataset?

I'm looking for public datasets of people wearing a device with an accelerometer (and potentially other sensors eg gyroscope or magnetometer). What are some of the largest available datasets like ...
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How to train a model to predict a time window than an event will occur on a website

I have a list of historical timestamps of when a specific event occurred on a website. Currently the timestamp represents a 30 minute window that the event happened within. I am looking to train a ...
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Import the same interval of previous week into the deep model

In a dataset, the data are the average of vehicles speed in the points (cells) of a map. I am trying to build a prediction model. While the inputs are the average of vehicles speed of all points in ...
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TimeDistributed Layers vs. ConvLSTM-2D

Could anyone explains for me the differences between Time-Distributed Layers (from Keras Wrapper) and ConvLSTM-2D (Convolutional LSTM), for purposes, usage, etc.?
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Keras - How to classify 1D time series

Say I have a training dataset composed by 128 1-Dimensional time series in form of numpy arrays. They all correspond to a certain action that I label action_1 and ...
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Representation based algorithms for clustering work for multivariate time series?

https://www.sciencedirect.com/science/article/abs/pii/S0031320305001305 and https://www.sciencedirect.com/science/article/abs/pii/S0306437915000733. These papers explain how clustering is made for ...
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Supervised learning for timeseries classification problem

I'm trying to use a supervised classification algorithm on a timeseries problem and my model is performing to well i think. It's a time to failure problem. I have 1000 sensors and have to predict if ...
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16 views

Time series: how to examine variance, stationarity, graphs?

I'm working with time-series and bank shares. I have difficulty analyzing graphs to find trends or stationarity in the data. I would like to apply the differentiation (first or second) to the data to ...
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Forecasting time series of binary vectors of given length

Please help me. I have a time series $$ x^{(1)}, x^{(2)}, \ldots, x^{(n)} $$ where $x^{(i)}=(x_1^{(i)}, x_2^{(i)}, \ldots, x_m^{(i)})$, $x_j^{(i)} \in \{0,1\}$, that is every $x^{(i)}$ is a binary ...
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25 views

how to find holiday effect on revenue?

I have 2 datasets from 2013-2017 for each day. a) Revenue generated by Locations and date. b) Holiday name and date I would like to know how each holiday is impacting the revenue by location. I am ...
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Input explanatory categorical variables along with time series into neural network

I want an advise on the ways to enter time series along with additional variables into convolutional neural network. Story first: I have a dataset of time series with daily energy consumption data (...
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31 views

LSTM regression bias increases when targets go close to 0

I've build a LSTM model for time series forecasting. Results are not bad, with a mean normalized error of 7%. However, this normalized bias shows a clear pattern: The closer to 0 the value to predict, ...
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20 views

Support Vector Machines for Time Series Forecasting [on hold]

I have dataset that has Temporal features as Day of week, Hour, Minute, Second, isWeekend and a target value (Y) that represent Number of requests I want to use SVR to predict Y. How can I do this ...
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Suitable algorithm for forecasting demand from mixed seasonal/non-seasonal data

I am new to data science and have an interesting forecasting challenge. Suppose I am a publisher of text books and related study materials (mock exam papers, revision notes and so on) for different ...
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15 views

Layman's explanation of when to use which smoother algorithm/technique: FFT, loess, Savitzky-Golay, etc

As an analytics practitioner, I frequently come across noisy data (e.g. IoT data). When building a model or machine learning algorithm, it can be advantageous to smooth this data. Over the years, I ...
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Which model can solve the “sequence demand”'problem?

I have a regression problem. When a truck comes, it influences the demand of employees for the next 30 days. Additionally the demand depends on the type of truck (when the truck is big, we need more ...
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Time-series analysis: Validity of Dickey-Fuller test with missings in data?

I have a huge (univariate) time-series dataset (100 MB), imported from Excel into Python. Column A contains a timestamp (over a 2-second window) and column B contains the value that was measured in ...
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On-line Time Series to Time Series Transformation

I'm a novice to ML, and I'm investigating methods for real-time transformations on time-series data. By "On-line" and "real-time", I mostly mean that, in it's application, all the data is not ...
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1answer
21 views

Using classification of previous sample in neural networks

I am trying to classify the state of a machine using different features coming from a set of sensors. I am treating the problem like a time series, so I windowed the stream of the sensors each X ...
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Input shape for simpler time series in LSTM+CNN

Following is code from https://machinelearningmastery.com/how-to-develop-rnn-models-for-human-activity-recognition-time-series-classification/ which uses LSTM and CNN with TimeDistributed for human ...
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1answer
42 views

Binary classification model with time series as variables

This is probably a simple question. Assume I'm interested in modelling a binary variable, with various covariates, including ones that are time series observations. In the usual modelling approach, ...
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1answer
38 views

How to apply Stacking cross validation for time-series data?

Normally stacking algorithm uses K-fold cross validation technique to predict oof validation that used for level 2 prediction. In case of time-series data (say stock movement prediction), K-fold ...
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2answers
37 views

How to learn from time series with multiple values for each time points

A multivariate time-serie has more than one time-dependent variable and it is my case. Still for each time I have not one entrie of dependent variables but many entries, like: ...
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1answer
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How to find similarity of two series over time containing periodic trends?

Considering the data is received from a streaming source each second.How to distinguish if both the line graphs 'look' same/different in real time, statically, like the picture given below Edit: 1....
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2answers
38 views

Branch of data science that covers event based time series?

Let's say I have discrete events in time, e.g. patients getting sick, and I want to predict whether theses events are indicators of some other underlying event, e.g. a disease outbreak. Usually, one ...
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22 views

Detect Missing Records in Dataset

I have a dataset that contains several measures from various widgets on a daily basis. While the widgets remain relatively stable over time, sometimes there are legitimate reasons for one to disappear ...
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Regression based on series of depth (similar to time series)

I have a data with set of independent variables and a target variable. The target variable is exponentially distributed based on the depth. Is there a way to identify a general depth function for my ...
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Using SMAPE as a loss function for an LSTM

I am currently working on a time series forecasting problem and am looking into using an LSTM. My final accuracy metric that I use to determine whether or not the forecast is good or not is defined ...
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Keras TimeSeries - Regression with negative values

I am trying to make regression tasks for time series, my data is like the below, i make window size of 10, and input feature as below, and target is the 5th column. as you see it has data of {70, 110, ...
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How to model machine learning problem for cache replacement policy?

I am trying to implement machine learning on Cache Replacement Policy. I want to train a ML model on labelled data acquire from Belady's Optimal Algorithm for Cache replacement policy. For example, ...
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2answers
37 views

How to model & predict user activity/presence time in a website

I need to make a prediction model based on some historical data from a website's user login system. Suppose my dataset has some features like user login time and logout time for each day for a ...
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Can an LSTM learn correlations between time series and produce skillful predictions for individual time series?

I am trying to build a model that is capable of producing a multi-step forecast for many different time series. To keep the example simple, let's say I have three different time series, $T_1$, $T_2$ ...
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How to compute server times from logs that have only mean response times?

I have a log where each entry has a timestamp, a number of requests that were processed since the last timestamp, and the mean response time for those requests. Assuming one CPU core and one infinite ...
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1answer
27 views

How to Identify p (lag order) for ARIMA Model in Python

here is my auto correlation plot. Generated by the following python code. ...
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1answer
26 views

Sequences of time series data with only 1 output classification

So I'm facing a problem where I have a sequence (30h of data with 10sec intervals) and which is labeled to a class (3 different classes) for the whole sequence. I'm used to work with time series who ...
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How to tune parameters for Time Series Analysis, when forecasting is only dominated by one feature and error is not getting reduced?

I am trying to predict time series based on 150 features. When I plot correlation of these features, I am getting 20 features with more or less importance but every model I use, it is completely ...
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1answer
40 views

Keras multi-label time-series classification considering time-series as an input image vector

I am trying to build a multi-class classifier using Keras. I am not quite sure I have implemented it correctly. Data is like this label time-series variables [0:25728} ...
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1answer
32 views

How do you detect seasonality(multiplicative or additive) in a time series data?

Trying to apply seasonal_decompose on timeseries data. It looks something like this: ...
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15 views

How to prepare data for time series RNN

I want to use RNN on my data. The data is from a number of medical devices, it is a time series. My problem is that there are few types of files, each having data from a deferent source: File #1: ...
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1answer
20 views

Input sequence ordering for LSTM network

When training a LSTM network with time series data, I guess the order in which this data is fed matters, my question is how should this ordering be... Let's take a time-series vector which will be ...
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1answer
26 views

Prediction: plugin a corelation table (neuron) into a Time-Series Neuron in Keras/ TF

i am adding more details I have a time series of Babies (1,2,3) showing how many problem they have each week (Born week 1 to week 80) and in which organ (14 organ). There is a separate numeric time-...
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Is it better to use a MinMax or a Log Return normalization to predict stock price movements?

I am trying to use a LSTM model to predict d+2 and d+3 closing prices. I am not sure whether I should normalize the data with a MixMax scaler (-1,+1) using the log return (P(n)-P(0))/P(0) for each ...
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1answer
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how to calculate number of datapoints within a given time interval?

I have a dataframe with one column which is a timestamp. I have converted that column to a datetime object using pandas to_datetime() method. However what I want is to ...
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1answer
71 views

Regex-style pattern-matching for time series

This is more of a "what technology/library would you use for this?" question than anything else. I have categorical time series data, and need to match cases in these time series to known patterns. ...