Questions tagged [forecasting]

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14 views

Forecasting Consumption for Multiple Products for Multiple Regions

Came across a very interesting Real-World Time Series Forecast Problem. Can you please help me understand the right track to resolve the below Time Series problem: Input Data Sample: and we want to ...
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2answers
18 views

Convey time lag information to a linear regression model

I am using a simple linear regression to predict the number of units an item has moved and price of the item is one of the input parameters. For a few items, the older prices are not relevant and ...
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1answer
77 views

Forecasting via LSTM or XGBoost… is it really a forecast or

I guess I understand the idea of predictions made via LSTM or XGBoost models, but want to reach out to the community to confirm my thoughts. This tutorial does a nice job explaining step by step of ...
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1answer
30 views

Forecasting time series outside the training/test set

I am trying to predict some time series based on precedent values using LSTM. I have pretty good results when I compare the predicted time series with the test set (0,18% error) I just miss how to ...
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8 views

What are good public datasets for time series analysis with “certified” (by papers in the literature) good predictors of the target variable?

I have to test different models for time series forecasting and predictors (exogenous covariates) goodness evaluation and I would like to use datasets used in relevant scientific publications that ...
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2answers
47 views

How to normalize a data set of multiple time series?

I have the a data set representing the electricity consumption of 25 000 customer. The electricity readings are taken from each smart meter each 15 min for a period of 3 days. The data is takes from ...
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1answer
12 views

How to measure/rate the effect of a exogenous covariate in a ARIMAX Model?

I have an ARIMA model, I'm trying to figure out how much an external variable (exogenous covariate) could improve the forecast, so I need to "synthesize" a rate that tell me the usefulness (or impact) ...
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18 views

How to understand logistic trend parameters proposed by Prophet (Facebook)?

I read the paper and I saw that the logistic trend is defined as below : $$ g(t) = \frac{C(t)}{1 + \exp{ -k(t) (t - m(t)) }} $$ Where $k$ and $m$ are respectively a growth rate and an offset parameter....
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17 views

LSTM forcasting: time series as input and a unique value for each as output

I am sorry for the mistakes I will make in this post, I'm new to deep learning ^^' I am trying to build an LSTM model that can help me predict some unique value according to time series indices and ...
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32 views

Problem with Prophet Model regressior

I am working on predicting half-hourly UK electricity prices with prophet. I have two other time series: gas prices and initial national demand out-turn. So, after merging all the data-sets together ...
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9 views

Context Dataset in Time Series Forecasting

In time series forecasting, what is context dataset? How different is it from the actual training dataset and what role does it play either in training or validation?
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46 views

How to combine data having similar distribution?

I have a collection of time series data with data points of around 2 years of daily data. I am thinking of a way to increase the number of data points in it so that the neural network gets a better ...
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1answer
25 views

forecasting - likelihood of customers participating in next month sales

I have historical transaction information of customers for the last 2 years and other information about the customers like what type of card (gold/platinum) they used for transactions etc. is also ...
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1answer
24 views

How to find feature importance with multiple XGBoost models

My problem statement : Time Series forecasting(Month wise data), training on 96 months of data and predicting next 12 months with a 3 months empty window in between. Example : Batch 1 ...
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0answers
25 views

Time Series and Statistical Learning methods differences

I am trying to understand the Time Series and Forecasting methods. I have this basic theoretical question about this: Why "Time Series" is NOT included on the Contents of, for example, the book "...
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7 views

Cross-validation for Timeseries Counterfactual Analysis

We are looking to predict counterfactual states from time-series data. In our problem we are looking to determine the energy savings from a grid-installed device that is varied on and off for many ...
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1answer
80 views

Forecasting multiple time series with a single model

I have a dataset with sales numbers for ~500 different markets (assume different cities or regions) and need monthly forecasts for each market. Instead of building 500 different models, I'm interested ...
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18 views

Why might an LSTM be capable of predicting an ARMA signal but not a linear combination of ARMA signals?

I have an LSTM network and am testing it on some dummy ARMA signals. I'm trying to predict the signal 5 time steps into the future. The network is capable of outperforming Naive (persistence) when ...
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13 views

For time series forecasting task, should I use data across several time steps or singe timing data for prediction?

I have a time series forecasting project, there are over 10, 000 time steps of data, so the data amount is not a problem. At first, I thought I've to create a time-based data pipeline that forms the ...
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6 views

How is possible the result of GRU would other way around compared to LSTM while they were implemented samely?

Recently I crossed to a situation I can't figure it out why it happened. I applied six predictive models on a specific dataset as training-set and tried to predict the other similar dataset as an ...
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1answer
38 views

LSTM with input of actual time step

I'm working on an implementation of LSTM neural network to forecast energy consumption. I have a dataset with load, series of weather parameters and indicator of it's bank holiday or not. I first ...
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1answer
61 views

How to make forecast in LSTM with specific/defined feature values

I am analyzing the avocado dataset to predict the future prices of avocado depending on the region and type (organic/conventional). I've trained my model which seems to be working. The test results ...
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27 views

How to time series forecast with multiple time series data sets on the same time series index

How does time series work with multiple time series data sets on the same index? For example, suppose I were a utilities company. Suppose I have the electricity usage of two homes, each indexed for ...
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20 views

How to get rid off differences between prediction and actuals while predicting or forecasting time series data

I have performed Boxcox transformation on my time series data and processed it through ARIMA modeling. Converted prediction values to the actual. I see significant differences between actual and ...
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9 views

What kind of feature engineering suits for random generation like time series data

My time series data looks like random generation which was obtained by aggregation day-wise sales of a product. The dependent variable does not show any kind of pattern. So have tried tries different ...
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1answer
30 views

How to forecast product/item sales next one week using Xgboost regressor

I have trained xgboost algorithm to predict the number of items sale on a given day and got pretty good results, now I would like to forecast sales ahead of one week. I tried re-training the ...
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36 views

Is it possible to use LSTM for time series forecasting for future months with test data having only NaN values?

my dataset is a univariate time series with one column as months, other column having demands for the corresponding months. My test dataset has NaN vals only for all the months. Can LSTM be used in ...
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1answer
54 views

How to split a dataset into train and test sets for time series (multiple step-multiple output forecasting)?

I am trying to use a LSTM neural net to do multiple step / multiple output forecasting (I predict multiple values in one time knowing some values in the past). But, I have realized that I must be ...
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0answers
10 views

How to get quantiles/probabilities of time series forecasts?

my problem is as follows : I am creating demand forecasts for some goods with different methods (ARIMA, ETS,..) The issue is that I would like to forecast the probabilities of those forecasts since ...
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9 views

What's the meaning of Err in Online Time Series Predicion with Missing Values

I'm reading THIS paper about online predictions on time series with missing values. And trying to code the third algorithm in C++. The thing is that I don’t understand what they mean by $Err_{\tau}...
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1answer
28 views

Building a time-series demand forecasting model

I am forecasting demand for certain types of goods and services, which I expect to be correlated to a sub-set of a basket of macroeconomic indicators (considering 15-20 indicators) I do not know ...
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34 views

Training multiple multivariate time series

I have just learned LSTM for one month, and I am doing a project that aims to train an LSTM model forecasting the taxi demand at "t+1" according to the taxi demand at "t", "t-1"... In particular, I am ...
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19 views

How to Manipulate date data for multiple visits per person?

I have a query to solve. I have data regarding customers and number of visits done to them. These are in two tables. So I want to join two table and create different features so that I can find better/...
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27 views

Finding p values and estimates of external variables in facebook Prophet for forecasting in Python

I am using facebook Prophet for multivariate forecasting which has an objecting of forecasting prices. My target variable is affected by n number of external variables too. I am using add_regressor ...
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15 views

A way to identify anomalous trends amongst several trends?

I'm working on a personal project, where I'd like to identify anomalous trends. Here's the scenario: Imagine a company can sell 3 types of say, candies: X, Y, and Z. For some reason, these prices can ...
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14 views

ARCH and GARCH model working and R code for its implementation

my time series data set doesn't have a proper trend or seasonality. Heard about ARCH and GARCH model which works fine on Un-trended data set but I am not finding the proper R code for its ...
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2answers
75 views

How to predict next visit date based on this data

I have a dataset shown below. Here, status is if visit has been done or not and schedule is if next_action_scheduled. ...
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0answers
52 views

Generalization of RNN/LSTM/GRU… model

Given a time-series prediction with a Recurrent Neural Network (doesn't matter if LSTM/GRU/...), a forecast might look like this: to_predict (orange) was fed to the model, predicted (purple) is the ...
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2answers
124 views

What arguments should I pass to input_shape parameter of LSTM function in Keras?

My dataset has 2944424 rows and 6 columns. I am using an LSTM in Keras to forecast taxi demand. I am having problem with the input_shape parameter of the LSTM. It ...
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0answers
20 views

What approach should I take to model forecasting problem in machine learning?

I have a dataset which contains 4000k rows and 6 columns. The goal is to predict travel time demand of a taxi. I have read many articles regarding how to approach the problem. So, every writer tell ...
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0answers
8 views

What is forecast horizon measured in?

I am using Microsoft Azure machine learning platform and when using the forecast feature it gives me the field of forecast horizon that uses an integer. Does the integer mean days, weeks, years, etc. ...
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1answer
45 views

Time Series Forecasting Seasonal type

As we all know there are two types of seasonal types, additive and multiplicative, but I have trouble telling them apart. To my understanding, in multiplicative seasonality, the magnitude of a ...
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1answer
113 views

Do we have to split our dataset into training & testing when using ARIMA model?

I am working on a project where I predict the total quantities sold at the ITEM/DAY leve. As for the model, I decided to with an ARIMA model (I'm using R). For guidance, I decided to follow the two ...
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0answers
25 views

Finding Outliers in Resource Forecast Data

Unsure if this is the correct place to place this, please close if so. I'm a workforce analyst at a large retail company, I own and maintain all the forecasting for our retail stores. This is based ...
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1answer
300 views

How to predict NaN (missing values) of a dataframe using ARIMA in Python?

I have a dataframe df_train of shape (11808, 1) that looks as follows: ...
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15 views

Compute error for each point the LSTM predict / epoch

I'd like to compute the error of each point my LSTM predicted per epoch. Example for 6 points predicted : epoch 1 : RMSE = [4,1,9,3,4,5] epoch 2 : RMSE = [2,0,6,5,3,6] etc. So at the end I can ...
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0answers
13 views

Standard for aligning data to week based on Mon to Sun for forecasting

I need to produce a forecast where i have predicted volume to a standard definition of a week. This definition is simply the week starts on Monday and Ends on Sunday. Is there an ISO standard that ...
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25 views

MAPE as an accuracy measure

I want to run and compare time-series forecast methods. Mean Absolute Squared Error (MAPE) is considered one of the strongest metrics for accuracy. My question is the following: If you do $1-MAPE$ ...
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23 views

if a time series is not stationary at a weekly level, is it also not stationary at quarterly level?

I have time series of sales of many products on weekly level for 2 years. I am interested in forecasting the sales on quarterly (4-months) level for every product. I also have some exogenous ...
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1answer
144 views

Time Series Forecasting for Multiple Customers using one RNN

I have a product which has univariate and also multivariate time series data from multiple customers. I have variable amount of data available. Ranging between couple of years to couple of months. ...