Questions tagged [forecast]
The forecast tag has no usage guidance.
95
questions
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19 views
Demand forecasting with marketing budget data
I'm trying to build a demand forecasting model to predict future daily orders of an online food takeout service (similar to UberEats or DoorDash). My first model uses a univariate approach, which is ...
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0answers
11 views
Demand Forecasting - Error in predictions
I've been trying to do daily demand forecasting using the H2O AutoML package for using 4 years of daily sales data as the training set. However, the daily estimates always seems to find a range around ...
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0answers
17 views
Impact of covid19 in forecasting models
I have sales training data from 2019-06 to 2020-06 and I have to predict sales from 2020-06 ...
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0answers
23 views
How to model a conditional demand forecast model as ex-ante forecast for a moving population?
Goal: I am trying to forecast demand from a specific population given a specific promotion on a certain period of time frame.
The data is of the format:
date | promotion % | sales in 1000s(y)
01-Jan |...
0
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2answers
36 views
Time series forecast for small data set
I am new in data science so please accept my apology in advance if my question sounds stupid. I want to do a time series forecast of outage mins in the current regulatory year. The regulatory year ...
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0answers
15 views
How can the forecast accuracy of three models for a categorical time series be compared?
This is a general question. Can anybody please point me in the direction of how I can compare the forecasts of a 3 level categorical time series by three competing models? I would like to compare the ...
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0answers
14 views
How to predict orders with a range of items?
So I do have data like this:
With the help of distinct order IDs, I can figure out how many orders are there and from units shipped, I can get the number of items in the order. Now I want to predict ...
1
vote
2answers
57 views
Low precision on classification model
I am working since some months on a prediction from lead to a sale. Someone makes a lead on my website and I want to predict if this user will make a sale. I have these metrics on the test data.
Now ...
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0answers
29 views
How to condition your neural network to seek a specific amount of output? [closed]
I transformed a time series with collection values from 0 to 100 into a windows of 60 elements with ...
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0answers
57 views
Why does the forecasting of this LSTM model look like a steady line?
This is a multivariate multistep problem using LSTM NN model. I am trying to forecast one variable by means of the other variables. However, the forecasting output looks like a horizontal line.
Kindly ...
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0answers
19 views
From daily prediction to hourly
I have daily number of sales prediction. I would like to go to an hourly level, taking this prediction. I have past data at hourly level. At this stage, I do not want to predict at hourly level since ...
2
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1answer
25 views
(Not a programming question) Is there a common word to indicate predict or forecast
The general understanding is:
Predict: past value - could be data the model has seen (data from train set) or past data model has not seen (data from test set) (together in-sample data)
Forecast: ...
2
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0answers
31 views
Time Series Analysis / Modeling with auto_arima
I recently dived into Time Series and was attempting at doing some data analysis and modeling. I'm using the following dataframe
...
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0answers
6 views
Ljung-box test on weekly percentage of total quarter bookings
I have a data on the weekly percentage of the total quarter bookings. The data looks as follows (note: weekly percentages add up to 100 for each quarter) :
(not real data)
I used the Ljung-box test ...
0
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0answers
21 views
Multiple Values for One Day
I have two questions.
1- I have weather data of 10 turbines and I know their collective production(Power).I also know maximum power a turbine can make. How can I forecast collective production if I ...
0
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2answers
26 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 ...
1
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1answer
58 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) ...
0
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1answer
128 views
Sliding window approach using SVR & LightGBM
I'm working on a multivariate time series forecast using a couple of ML algorithms (Neural Networks, Support Vector Machines & Gradient boosting algorithms). I need to measure the performance of ...
2
votes
1answer
395 views
ValueError from statsmodels ExponentialSmoothing
I've been having a frustrating issue with the ExponentialSmoothing module from statsmodels.
My data is a pandas series with 74 weekly data points that looks like this:
...
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0answers
2k views
How to fix “'The `start` argument could not be matched to a location related to the index of the data.” Error?
When I try to predict the results using ARIMA for a specific train/test split, its throwing an error like this:
"'The start argument could not be matched to a ...
1
vote
1answer
4k views
Auto.arima with xreg in R, restriction on forecast periods
I am using the forecast package and implement auto.arima with xreg. Here I want to forecast ...
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0answers
45 views
How to interpret the graph representing the fit provided by the ARIMA model?
I'm following this tutorial here to build an ARIMA model in R.
I've done a Forecast using a fitted model in R. I specified the forecast horizon h periods ahead for predictions to be made and used ...
0
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0answers
14 views
How to explain calm period in energy consumption
I have a dataset of energy consumption that looks like this:
I got it from Kaggle.com and all it says is that it's energy consumption data from PJM (this is the PJMW_hourly that corresponds to the ...
3
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1answer
66 views
Next year forecasting with monthly data from many, correlated, non-monotonic trends
I have trend data from many health departments in a local territory (eg. cardiology, orthopedics, etc...). These trends represent health service (visits, diagnostic, admissions) production, service ...
1
vote
1answer
39 views
How can I go about building a model for large number of outputs?
I have previously worked on small-scale feedforward neural network problems.
But I have started working on a new project where the goal is to predict air quality in 25 locations throughout the ...
1
vote
0answers
68 views
Model for time series analysis
I'm new to data analysis and ML in general. I'm working with some friends on this problem: We're trying to predict when a component of a machine will stop working properly so the client can change it ...
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0answers
138 views
Predicting Wave Trends of Candelestick Charts in Tensorflow (JS)
I'm relatively new to ML but my goal it to use Tensorflow.js and build a ML model that can help me detect a certain wave formation for an automated trading system. Examples of the 3-leg pattern I am ...
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votes
4answers
22k views
Additive vs Multiplicative model in Time Series Data
The above time series plot is a daily closing stock index of a company. I want to know which model between additive and multiplicative best suits the above data. I know what the two models are, but i ...
2
votes
2answers
492 views
Analysis of Time Series data
The below graph is a scatterplot of daily stock price. My aim is to predict future stock price of the company.
From the scatterplot it seems that it is a multiplicative model, so I tried to "...
1
vote
0answers
38 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 ...
2
votes
1answer
83 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....
0
votes
1answer
26 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:
...
1
vote
0answers
59 views
Tuning a sequence to sequence model
I have written a variable length sequence to seqeunce autoencoder in keras using this tutorial as a guideline: https://blog.keras.io/a-ten-minute-introduction-to-sequence-to-sequence-learning-in-keras....
4
votes
1answer
161 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 ...
4
votes
1answer
3k views
Monthly trend with fb prophet-Interpreting the graph
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 ...
1
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0answers
30 views
Specific data formatting techniques for discontiguous time series?
I'm facing a predicting problem for food alerts. The goal is to predict the variables of the most probable alert in the next x days (also any information I could get about future alerts is really ...
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0answers
21 views
Observation Operator - Data Assimilation
In data assimilation, one assumes the existence of a observation operator $\mathcal{H}$ that maps the model-state vector $\bf{x_b}$ to $
\bf{y_b}$ (the model-equivalent of the observations $\bf{y_o}$) ...
1
vote
1answer
32 views
Strategies for continuously assessing and improving model performance
I am building a supervised machine learning model to generate forecast.
So I would have historic data like this:
SKU, Month, .... other features, Actual Volume
...
1
vote
1answer
2k views
How to calculate prediction error in a LSTM keras
I have an LSTM which I have constructed and run in keras using python. I use this model to predict $n$ points into the future for a time series forecasting problem.
When I use a method such as ...
1
vote
2answers
85 views
What are some appropriate models to use for inventory forecast based on consumption history or trends?
I am working on an inventory management system where I have daily/monthly/yearly consumption history for a particular item, which may or may not follow a repeating trend. In order to forecast demands ...
0
votes
1answer
31 views
which forecasting models could be chosen?
I'm new for data analysis. I got some data from the regional environmental center.
Measurements:
Datetime, PointID, SubstanceID, Value (substances concentrations in air), MeteoID ,NextValue
...
1
vote
1answer
123 views
Fully endogenous models for predicting multivariate time series
I have a formal social science background but I am new to data science. My interest is in building predictive models for applications in the social sciences, mostly (but not only) in economics.
I am ...
1
vote
1answer
591 views
demand forecast for B2B
I am attempting to create a demand forecasting model in python to predict future sales of a particular category of product, using historical sales data.
We are a B2B company, which means that we ...
1
vote
0answers
128 views
Naive/ Persistent Models & 7 Day Forecasts
When determining the baseline performance using a persistent or naive model I understand it to be using the value of the previous time step as the prediction for the next time step and then ...
0
votes
1answer
226 views
A timestep's prediction depends on future data
Consider an LSTM model with 100 timesteps, each of which with input and target data. Let f(99) be the function mapping the input data of the 99th timestep and hidden state of the 98th timestep to the ...
0
votes
1answer
533 views
Modelling promotions for demand forecasting
I am trying to develop a model to predict future demand for a product. Now, there are always some promotional events that affect the sales. I am trying to solve this problem using dummy variables. ...
0
votes
2answers
771 views
Fitting an arimax model on out of sample dataset
I have built an arimax model where we have sales data across time as the response variable and price is one of the external variables. I used the below code to build a simple arimax model. I had data ...
4
votes
1answer
2k views
Time series forecasting using multiple time series as training data
I am trying to forecast the total attendance (ie. the number of entrances, which is also the number of tickets bought) of a festival just two days after it started. That is, knowing how many people ...
0
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3answers
480 views
Forecast vs Prediction: What is the difference?
I use the two terms as follows:
A prediction model gets features (which can be a time series) as input and gives a fixed-length output (might be multiple values, but "atomic" in some sense)
Examples:...
2
votes
0answers
4k views
