Questions tagged [forecasting]
Forecasting involves estimating values (or distributions) that have not yet been observed.
forecasting
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Optimizing pandas performance on large datasets
I'm working with a large dataset (~10 million rows and 50 columns) in pandas and experiencing significant performance issues during data manipulation and analysis. The operations include filtering, ...
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setting an array element with a sequence requested array has an inhomogeneous shape after 1 dimensions
As I was fitting various artificial neural network, the code for TLNN was shown as incorrect especially the line containing the reshape function. Is there anything wrong with this?
def forecast_TLNN(...
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How to improve SARIMAX model to forecast more accurate?
I am new to forecasting data and seeking for suggestions and guidance. My goal is to forecast sales of product at the end of the month using SARIMAX model. The dataset given is daily date with ...
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forecast payment terms by calculating payment by month and stop calculating on need date
I'm trying to forecast payments into the future and calculate the cost per month from the order date to need date and stop calculating the month of the need date. I'm tracking multiple orders under ...
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Forecast Model and exog
I am currently working on a time series task related to predicting the AI demand in the market. I have already obtained the monthly percentage of AI jobs relative to total jobs from 2018 to 2023. I ...
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Time series forecasting over Fashion trend [closed]
Dataset I'm working over
I want to do fashion forecasting Over this data and I want to forecast the product_name over time, I was thinking to use prophet library but it can only handle univariate ...
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Why are my SARIMA model forecasts all NaN in the DataFrame?
I am working on a cash flow forecasting project using Python and the pmdarima library for SARIMA model predictions. I’m able to generate predictions for each column and print them, but when I try to ...
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Could we impose to a SARIMA model that the sum of predict values equals a given value (in R)?
I work on a forecasting R model (SARIMA) with monthly time series data. However, for the last year of my training data (2023), I don't have the details by months but I have the annual value.
I want to ...
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forecast does not use the date range set by sample command
I have a workfile with a range of 1999-2024 , inside it I have series with different starting and ending dates.I am running an ls regression equation for a smaller sample smpl "2015 2015+1000&...
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High Error Values with Optuna in SARIMAX Parameter Optimization
I'm encountering issues with the SARIMAX algorithm while using it to forecast 1-step customer demand. The problem is that the error in the trials is very high, resulting in a large MAPE and RMSE (...
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Appended TimeSeries must start one time step after current one
Im getting the error
ERROR:darts.timeseries:ValueError: Appended TimeSeries must start one time step after current one.
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Why does my forecast/prediction using a VAR in statsmodels quickly converge to zero?
Outline: I am using a vector autoregression (VAR) model from the statsmodel package https://www.statsmodels.org/stable/vector_ar.html#var.
My two time-series, let us call them time-series 1) ts1 and 2)...
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Microsoft ML .Net Forecasting Model backtest usage issue
I am new in ML .Net Forecasting. I am trying to build a simple application for Prediction.
Time Series (step is 1 month, 1993-1995),
Data = values incrementing with step 10 starting from 100.
Then I ...
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How can I model to predict decay trend based on intial 5 equally spaced rate of changes at 1 minute interval?
I have 30 decaying traces. Each of them has slight different rate of change. I want to model (classical or RNN) based on 5 initial rate of changes after every 1 minute. So I have R1,R2,R3,R4,R5 till ...
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I want to predict stock price in next 60 days by machine learning
I wanted to predict stock price in the next 60 days but after I finished writing the code, it predicted backward instead. Can anyone advise me? How can I do it? I revised my code but it's not working.
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