Questions tagged [forecasting]

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24 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
177 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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102 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
262 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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21 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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9 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
47 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
314 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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1answer
40 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
727 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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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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43 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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37 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
305 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. ...
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158 views

How to apply an RNN to forecast non-stationary time series?

Is it possible to predict a time series which is non-stationary, in the sense that, the dependent variable Y have an increasing trend? Therefore, the highest value of $Y$ in the training set may be ...
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1answer
51 views

In which CRAN mirror is the quadprog package available?

I was trying to find the accuracy of some predicted data and I came to know that I can use the forecast package to do this. When I installed it and gave library(forecast), it said it needs quadprog ...
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69 views

Dummy/baseline models for time series forecasting

I am working on an evaluation of time series forecasting models in Python, more specifically with statsmodels, scikit-learn and <...
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131 views

predictive clustering trees in Python?

I am faced with a time series forecasting cold-start problem, specifically I am forecasting energy consumption of businesses where historic consumption data is available only for training but not new ...
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1answer
35 views

How to forecast time series analysis for more then one dependent variables?

I have three datasets: Dataset_1= column name as ID, Date, counter_id Dataset_2= column name as ID, no. of tickets sold ...
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1answer
276 views

Training a LSTM on a time serie containing multiple inputs for each timestep

I am trying to train a LSTM in order to use it for forecasting : the problem is basically a multivariate multi-steps time series problem. It is simply an experiment to see how statistical models (...
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2answers
72 views

Time-series forecasting

Here is the data: ...
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1answer
84 views

Training data : forecasted or actual?

I am working on a time series prediction problem. I am using keras models for machine learning. For this prediction, weather variables are used as input. They can be of two types: forecasted and ...
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0answers
85 views

What's the difference between ELM and NNAR?

I'm working with time series forecasting using the two techniques that involve neural networks, the Extreme Learning Machine and the Autoregressive Neural Network. Reading the two methodologies, the ...
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31 views

Can I forecast with discontinued data using ARIMA?

I have data for sales on monthly basis, but a few months' information is not in the CSV file or data file. Can I forecast or fill that missing month with other calculated values from present records? ...
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0answers
76 views

How to model non-linear demand function?

I am trying to build a dynamic pricing algorithm on intermittent data (a lot of zeros between non-zero values). I have on average 100 non-zero data points for each product. However, it seems to be ...
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1answer
72 views

What Predictions can be done for Restroom/Washroom Data? [closed]

My company has installed sensors, which actually monitors the Restrooms/Washrooms in the Building. Currently the sensors collect data such as Ammonia, Nitrous and Visitors Count; All the data ...
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17 views

How can I enrich train data in case of cnn using target and time features

I have a sequence of images, let's say we ignore time specificity for now. In the other hand, target is a multivariate continuous time series. Let's consider it just a univariate one. Training a cnn ...
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0answers
59 views

LSTM - Forecasting usage (real world) [closed]

I see that LSTM is very powerful reconstructing time series it was fed with, but my issue is: => Can LSTM predict future values without requiring real (training/testing) data? My objective is simple:...
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33 views

forecast product demand in one week using machine learning approach

I'm trying to predict product demand in store. The predictors I have include price, competitor's price, store ID, date. My target variable is sales volume (in a particular store). What I need to ...
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1answer
66 views

how to predict content based demand

this is my first post at ds StackExchange, so please be gentle and let me know if something is not clear :) I have many products (>1M), and I save all the products purchases in a DB with a time stamp....
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1answer
2k views

Is there an R tutorial of using LSTM for multivariate time series forecasting?

There is a great blog post about how to use keras stateful LSTM in R to forecast sunspots. I applied it to financial ts data ...
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58 views

Long run time for grid search SARIMA

I am running a grid search for identifying the right set of params for Seasonal ARIMA, for over a 1300 training set and range for all the params being 0,1 and 2. But this process is taking over ...
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1answer
22 views

ML technique to predict next year output based on text quantities [closed]

I have a random data that I would like to predict how much a quantity will be in 2020. The data looks like this: ...
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1answer
348 views

How to calculate customer purchase interval and predict next purchase in python?

Suppose we have a data set consists of columns TransactionId, CardNo, TransactionDate then how can we calculate the customer purchase interval (means if customer A purchased on Jan 1st and after ...
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38 views

Curve fitting with R

I was wondering if there is a package in R for fitting a non-symmetrical bell-shape curve?
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1answer
82 views

Is an Arma model equivalent to a 1-layer Recurrent Neural Network without activation function?

Given a time series $f(t)$ to forecast, let us consider an Arma model of the form: $$ f(t) = c + \sum_{i=1}^p a_i f(t-i) + e(t) + \sum_{j=1}^q b_j e(t-j) $$ where $e(t)$ are the forecast errors. On ...
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0answers
2k views

Monthly trend with fb prophet

I have monthly data with month/year in one column and price on another. I would like to get a yearly trend with fb prophet library in python (how to use monthly data with the library is explained at ...
2
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1answer
120 views

Forecasting energy consumption with no historical data when there is a trend

I want to forecast new customers' energy consumption. Let's say I can construct a set of attributes to describe new and existing customers (e.g. size of business, type of business etc.) and I have the ...
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0answers
1k views

Understanding how to use ConvLSTM for multistep ahead forecasting

I have a problem where I have transaction data for many banking accounts. The task is to train a model on historical debit/expense transactions and then forecast expense transactions for the next n ...
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0answers
510 views

Recommended model for univariate or multivariate multistep ahead time series forecasting

I have a dataset consisting of recurring and non-recurring expense transactions from bank accounts, as well as other features describing the bank account and each transation. I aggregate these ...
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0answers
40 views

What is the correct format of the test input for LSTM neural network? [closed]

I have learned some tutorials for LSTM time series prediction. According to that tutorials, My training data format would be like, NOTE : This data is only for example. this is not the real data. <...
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1answer
140 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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2answers
612 views

Multivariate VAR model: ValueError: x already contains a constant

I have already read this question and the associated answer. I have removed any 'all zero' columns, as recommended in the answer. I have 3,169 columns remaining. ...
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1answer
20 views

Autoregression with multiple factors

I am not sure if this is the right place to ask this question. Anyway, I am working on a Forecasting using spending data. Using autoregression, I am able to predict the following number decently well ...
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0answers
42 views

What kind of algorithm should I use to build ML model that can predict just next reoccurence of an event in the future (at irregular time interval)?

I'm quite new to machine learning and statistics. I've a dataset from some ecommerce sale's history. It's almost 2k instances, and features include personId (string), productCategory (string/...
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1answer
81 views

How is PACF analysis output related to LSTM?

I was going through a recent paper “A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature ForecastingUsing Long Short-Term Memory Neural Network Based on Ensemble Empirical ...
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2answers
980 views

LSTM future steps prediction with shifted y_train relatively to X_train

I'm trying to predict simple one feature time series data with shifted train data. The source looks like this: ...
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2answers
50 views

How to predict weather? [closed]

I want to know how does one predict day to day weathers. Like what are the factors that must be known to predict day to day weathers using a NN. Few factors I could think of are: Humidity Weather ...
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0answers
34 views

Can ARIMA be applied on a dataset of few months?

I have dataset of a few months of (time series) electrical load usage of multiple users. Can/Should ARIMA be applied for load forecasting considering that its not much data?