Questions tagged [forecasting]

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VAR model ValueError: x already contains a constant

I'm using VAR model for multivariate time series. The structure is that although each variable is a linear function of past lags of itself and past lags of the other variables, one and/or two of the ...
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2answers
1k views

forecasting revenue

Does anyone have any recommendations on how I would go about forecasting Microsofts revenue using python + time series or ML (recommended techniques e.g Random-forest). (I have past revenue and share ...
9
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1answer
4k views

Can Reinforcement learning be applied for time series forecasting?

Can Reinforcement learning be applied for time series forecasting?
2
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1answer
470 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
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1answer
41 views

How to utilize user survey answers and the actual usage in forecasting power usage using LSTM?

I have the pre-trial survey and post-trial survey conducted of around 5000 users for Smart Meter installation. With this I have power usage reading recorded every 30 min for around one and a half ...
0
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1answer
182 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 ...
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0answers
92 views

Analysing spikes in demand to forecast future demand

I am trying to develop a system to predict future demand for different products at my firm. Currently, I have about two years of weekly sales data of a single product. My target is to predict the ...
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0answers
25 views

How to decide which forecasting model to use? [closed]

So I have a sales forecasting problem where I have 3 years worth of data about weekly sales of a certain company. There are 3 types of retail stores in that company, Type A, B, and C. There are a ...
1
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0answers
186 views

Predict the probability that a customer buy today

My company sells a single product that is a commodity. If you buy it, I can be sure that you will buy it again in the near future from me or from my competitors. The demand is affected by the weather. ...
4
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1answer
1k 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
201 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
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1answer
99 views

How do I use rnn to forecast to n periods with limited data?

So this is my 1st time trying to run a small time-series dataset through an RNN, but after a lot of searching, I haven't been able to find, 1. How I can use this to forecast to n periods ? (like in ...
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0answers
3k views

Error when using seasonal arima in python

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2
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1answer
144 views

How to predict next year's gross revenue given this year's data?

I have the following dataset (.csv format) which contains: 100 columns: $\textbf{Period}$ (in years, e.g. 2017, 2018, ..., 2028), $\textbf{Gross Revenue}$, $\textbf{Region}$ (e.g. APAC, NEMEA, etc), ...
3
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1answer
582 views

how to decide categorical variables for prediction

I have a dataset that contains weekly sales for stores and categories. It looks like this: I would like to apply gradient boosting method to predict weekly sales. My question is: Should I create ...
1
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1answer
35 views

Last cell in recurrent network always the most accurate

I am using a recurrent network for time series forecasting. The prediction from the last cell in the network always seems to be the most accurate. For example if I have 20 cells (so my input samples ...
1
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0answers
38 views

What values should I choose for P and Q?

I am trying to forecast energy data generated by LoadProfileGenerater. This data is generated every half hour for 2 years. I am following this tutorial. I have checked it for stationarity using ...
11
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1answer
9k views

How to Predict the future values of time horizon with Keras?

I just built this LSTM neural network with Keras ...
3
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1answer
95 views

What are the prerequisites before running Holt Winters Model?

I just read Demand-Driven Forecasting: A Structured Approach to Forecasting(Wiley and SAS Business Series) and have a few doubts in Holt-Winters Model: 1) Unlike OLS Regression Modeling technique or ...
4
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2answers
965 views

Forecasting Multiple (few hundreds) uni-variate time series with inflated zeros

Hello Practitioners, Being a newbie seeking help to gain experience in Data Science. Lets take a scenario where a big company wants to forecast its sales(a specific product) across different ...
1
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1answer
3k views

time series forecasting - sliding window method

I have been trying to understand this sliding window technique but to no avail and really unsure as to how I would implement it. My dataset: I have hourly values for the electric load for a year (...
0
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1answer
52 views

Need recommandations of using timing variables for forecasting sales

I have a data.table that contains many timing variables. Date: it gives the date of Sales Promo2(week, year): It describes the calendar week and the year when the store has started to participate in ...
2
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2answers
139 views

How do I arrange my data to predict 6 weeks of daily sales

I have a data.table base that has many variables to use them to forecasting sales for the next 6 weeks of daily sales. In fact, all the database is arranged by date as you can see here.Note that here ...
3
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1answer
116 views

When forecasting time series, how does one incorporate the test data back into the model after training?

When you build a classification or regression model, you typically split the data into a train data set and a test data set. The test data is a randomly selected subset of the overall data. Once you ...
1
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0answers
359 views

Spark fitting into Data Science Paradigm for timeseries data

I have seen Dataframe as new API on Spark2 instead of RDD.So I have following few question about the utility of Spark in terms of time series data. Is forecasting still limited to memory available in ...
1
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1answer
305 views

Long term time series forecasts with small dataset

I have a small dataset which has timestamp and temperature values for 6 months(I.e. one temperature value per day). I would like to forecast 2-3 months of temperature. I would like to know, what kind ...
1
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2answers
379 views

Input for Sales Forecasting

I want perform demand forecast for particular item based on attributes.Did I need to train the model with unsold items ? by maintaining sales Quantity as zero or go with only items sold in training ...
0
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1answer
1k views

Predict next series of numbers based on previous data

I have the following list of numbers (1 – 5 categories, first row) that I am trying to predict the next sequence for each column (total column sum = 6). There are over 1,500 lines of data in total. I ...
1
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1answer
182 views

Choosing the right model for predicting demand

We have a data set of 300,000+ records that looks something like the following: ...
2
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1answer
86 views

Aggregation of Discount

I am trying to predict sales quantity of an item based on their attributes. Discount is one of those attributes. The problem is I am having different discounts in same period for same item .I need to ...
0
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2answers
904 views

Simple Time Series Prediction

I have a data set like this. Here the first column is date, the second column is Temperature, third one is humidity, fourth and fifth column are two other boolean data. I have data of 6 years like ...