Questions tagged [time-series]

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

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11k 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 ...
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6 views

Multivariate time series forecast with VAR confusion

I am new to time-series forecasting. I am working now on a task in which I have a data set, containing samples of approx. 15 variables for every hour for several years. Then, I have a test data set (...
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10 views

How to train a NN with mutliple variables? [closed]

I have a csv file with following content (the full list has more entries): ...
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1answer
21 views

Multi-output, multi-timestep sequence prediction with Keras

I've been searching for about three hours and I can't find an answer to a very simple question. I have a time series prediction problem. I am trying to use a Keras LSTM model (with a Dense at the end) ...
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1answer
32 views

Similarity between two time series with different sampling frequency, different amplitude, and different lengths but taken from the same source?

I have two files with accelerator readings and I want to get some metric/ measurement to get the similarity between these two files. I have tried Pearson’s R coefficient, dtw distance, dtw score. ...
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11 views

Time series forecasting in Python with 2 categorical variables

What approach is the best for a time series forecasting where you want to include 2 categorical variables in python? Im not finding any useful information that can help guide me with this; mainly ...
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20 views

how to use CNN-LSTM with timedistributed

I am trying to use CNN-LSTM model with keras to reconstruct the time-series images, but now there are some weird problems. The input image is gray-scale and the input shape is ...
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1answer
46 views

Time Series Continuous Classification

Intro I'm quite new to all the subjects in this question. This is my very first shot at Keras, Tensorflow, NNs or Time Series. If you're not a newbie, you'll notice that immediately. Problem I have ...
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9 views

Which statistical tool, for test of hypothesis, is appropriate to find p- value in a python time-series data? [closed]

I have a long-term timeseries dataset with hourly time resolution. I found daily average values for each day in a week. I could clearly see some weekly variation. But, I want to ascertain that the ...
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2answers
28 views

Low scale ML/statistical techniques for data poor settings

I have two separate problems. One is logistic regression and other is time series prediction. But both suffer from paucity of data problems a) For logistic regression, I have tiny dataset with 10 ...
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9 views
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2answers
193 views

What are some good methods to forecast future revenue on categorical and value based data?

I have monthly snapshots (3 years) of all the contract data. It includes following information: Contract status [Categorical]: Proposed, tracked, submitted, won, lost, etc Contract stages [...
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1answer
376 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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1answer
374 views

Architecture for multivariate multi-time-series model where some features are TS specific and some features are global

I'm looking to build a time series model (using a TCN or a LSTM) with $N$ different series, each of which has $P$ series-specific features $\mathbf{X}$. My input array is of dimension $N \times t \...
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340 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 ...
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11 views

Finding the wiggles pattern in the original dataset. (Wiggles appear after performing division by another dataset)

I have multiple measurements regarding scientific observations. The problem is that there is a subtle noise pattern caused by the instrument - the wiggles. These wiggles are invisible when looking at ...
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6 views

Forecasting mon missing time timeseries data

I have time series data for minutes interval. But due to some noise i have to remove some rows from data. Now, I have data with some missing time stamp. What should i do for forecasting in this case?
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1answer
29 views

How an input data flows through an lstm layer cells?

I make this sec2sec NN model for the purposes of learning: ...
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1answer
207 views

Anomaly detection - relation between thresholds and anomalies

I'm developing an anomaly detection program in Python. Main idea is to create a new LSTM model every day, training it with the previous 7 days and predict the next day. Then, using thresholds, find ...
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1answer
37 views

Facebook Prophet add Regressor

I've been searching for a long time to answer my question, but I haven't found anything. So I hope you can help. I'm searching for an opportunity to add a regressor to my prophet model in python. I ...
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2answers
149 views

How to define tidy data if there is repeated measures?

Some time ago I read R for Data Sciece and there is the following definition of tidy data: There are three interrelated rules which make a dataset tidy: Each variable must have its own column. Each ...
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1answer
24 views

how can we feed both data time series and non time series data together in machine learning classification model

I have a dataset(IoT wearable dataset) composed of time-series and integer data; the objective of my task is to use the dataset for classification. Whilst current libraries in sktime accept ...
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3 views

Tier Splitting for Time Series Analysis K means

I am currently trying to expand upon some results from the paper "Time Warping Clustering for the Forecast and Analysis of COVID-19" by Qixuan Jin out of Cal Tech, because when it was ...
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2answers
76 views

Sourcing (discounted) products customers want

Goal: Generate a list of 100 products per vertical (e.g. fashion, electronics) that the teams should source, discount, and list on the website over a specific period. You may assume all customers are ...
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1answer
29 views

How can I split hourly time series?

I'm newbie in R and time series analysis. I'm trying to build an Arima model. My dataset has this structure: ...
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11 views

In Time Series forecast, should Scaling be done on both train and test features combined ( test is 1 new data point)?

Let say I have a Time series, I'm using sliding/expanding window method to split to train and test data: train would be all the data I have until day x and test is day x+1. To avoid Data leakage I'm ...
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2answers
68 views

Detecting abundance of a certain periodic pattern in a time series?

I am really stumped at the moment about how to solve a particular problem. I have many time series like this: This represents the number of hours a person spends on a website each day throughout the ...
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2answers
31 views

How to convert longitude and latitude in time series data from daily to weekly?

I have time series data like this: date longitude latitude 01/01/2010 -5.42766 107.5784 02/01/2010 -6.42728 104.5245 07/01/2010 -7.42702 105.5816 14/01/2010 -4.42728 99.57834 17/01/2010 -6.41523 ...
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3answers
192 views

Cluster evolution over time

I have a dataset of transactional data with customer ID and I want to segment the dataset into groups using cluster analysis. I'm interested in following the evolution of each cluster over time, but ...
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21 views

Machine Learning Model for Time Series Forecasting

I am using Random Forest, SVM, and XGBoost models to nowcast/forecast an economic time series variable. However, I would like to extend these models to optimize/customize them for time series ...
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1answer
3k views

Agglomerative Hierarchial Clustering in python using DTW distance

I am new to both data science and python. I have a dataset of the time-dependent samples, which I want to run agglomerative hierarchical clustering on them. I have found that Dynamic Time Warping (...
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22 views

One Year Ahead Forecasting with Unevenly Spaced Time Series

I have many products in my warehouses which can be "demanded" any day by my different clients. I want to forecast how many of each item will be demanded for the whole next year. Naturally, ...
2
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1answer
35 views

LSTM for time series forcasting

I manipulate the time series using the different structures of the neural networks in order to make a prediction, and I wonder if there is a way to choose the parameters of the networks intelligently? ...
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6 views

time series prediction training on multiple lags using tensorflow 2

I am just studying tensorflow 2. Here is where I learned time series training on multiple lags using LSTM: https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/ In this ...
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14 views

How to fill missing latitude and longitude values in time series data?

I have time-series data like this: date longitude latitude 01/01/2010 -5.42766 107.5784 02/01/2010 -6.42728 104.5245 07/01/2010 -7.42702 105.5816 14/01/2010 -4.42728 99.57834 17/01/2010 -6.41523 ...
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1answer
3k views

Variational Autoencoder TIme Series

Can anyone suggest a blog where Variational Autoencoder has been used for time series forecasting?
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0answers
21 views

CNN regression. help to improve current model [closed]

I have time series grey scale images that show movement of fluid with different densities. I want to predict a pixel value for time t, with (t-3),(t-2),(t-1) 2D images as inputs. I am figuring out how ...
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5 views

Multiple step prediction for non-time series

I have a public EHR dataset which contains info on a) lab tests b) diagnosis c) surgical procedures d) drugs prescribed etc Now, using the above data elements, I would like to predict the below a) ...
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0answers
278 views

ARIMA forecast for timeseries is one step ahead

I'm trying to forecast timeseries with ARIMA. As you can see from the plot, the forecast is one step ahead of the expected values. I read in some other threads that this behavior is expected but how? ...
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1answer
42 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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1answer
52 views

How to manage missing data in meteorological time series?

How to know the type of missing data is what it is: MCAR, MAR or NMAR, knowing that I'm working on time series multivariate, and is that going to help me deal with the missing data, and what is the ...
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1answer
128 views

Python: SARIMAX Model Fits too slow

I have a time series data with the date and temperature records of a city. Following are my observations from the time series ...
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1answer
30 views

M1 MacBooks versus Google Colab

I am just starting getting into deep learning with tf.keras. I am at the point where I have to decide where I want to develop. The thesis project will be timeseries ...
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1answer
204 views

Problems to understand how to create the input data for time series forecasting with a recurrent neural network in Keras

I just started to use recurrent neural networks (RNN) with Keras for time-series forecasting and I found this tutorial Forecasting with RNN. I have difficulties understanding how to build the training ...
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1answer
48 views

Using sensor data and a know reference point infer the position of a moving robot

Say, the robot is starting at a known position and I've data coming off of the robot as it traverses the grid layout. Exploiting the nuances captured in the data - like the implication of unequal rpm ...
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ValueError: Found input variables with inconsistent numbers of samples: [367, 24]

Working on a Time Series model that was 730 days with of revenue data and I have two questions. First, I'm a little confused on how many days I should set my train and test split to. Currently, it's ...
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1answer
13 views

X Second samples taken on unevenly spaced intervals

I have dataset of following specification: 512 samples taken at unevenly spaced intervals over the year Each sample is an 8 second data from sensors with 4ms resolution Samples are not labeled For ...
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12 views

Data augmentation for tabular data in a multi label classification task

The task at hand is to predict the future lab values for a patient (1 if abnormal and 0 if normal) using the previous numerical data. It is a multi-label, multi-class time series classification task. ...
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9 views

Is it Worth Installing Cesium on Windows?

I am using Python(Anaconda package). I know Cesium requires a Cython and a C/C++ complier because I have a windows computer. I was looking at the installation instructions and it appears to be ...

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