All Questions
Tagged with machine-learning time-series
496
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Using LSTMs for Predicting Targets with Known Feature Vector
I am trying to use an LSTM to predict the consecutive "offset" calibration values for an instrument. These offset values have previously been shown to be well correlated with a pair of ...
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53
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7
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Is this recursive forecasting right for timeseries analysis?
Training a model just to make a quick prototype
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13
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How to predict Future CPU Usage in Time Series reusing your already trained model?
I'm currently working on a time series problem where I need to predict future CPU usage. I have historical data consisting of CPU usage along with features like hour, day of week, and month. However, ...
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30
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How to explain missing dates to a model?
I have this dataset that I'm trying to train a neural network on.
The problem is that since weekend dates are not available, I am not confident in whether the model is able to account for that. ...
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34
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Can anyone help me understand this problem in my data?
I tried making a model using the autoTS library but the thing is in the result it gives me the following results. I checked everything there is no missing data but the original data had a missing ...
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1
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158
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Optimized input data structure for ML model training
I have a large dataset (20M+ rows) of user interactions which I want to use to predict the probability of a customer purchasing an item in one-, three- and six months time. However since the ...
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35
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I need suggestion for a project
I want to make a forecasting system which will forecast how much quantity will be sold next year based on the previous 5 years' data from 2019 to 2023 and want to predict for future years. Now the ...
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15
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Whats a suitable feature selection method for Time series data across multiple files?
My problem is basically a higher dimensional regression, where my input is (100 levels, 300 timesteps, 23 features)
My goal is to build a deep learning LSTM model that finds which level the data ...
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23
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Should I standardise time series data for deep learning classification?
Say I have time series data for classifying stars using deep learning based on stellar variability, with each time series data measuring the flux of the star overtime. For each star, I have the data ...
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34
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Forecasting Resource Depletion in a Distributed System
I manage a distributed system where each node contains six interchangeable resource slots, sourced from a diverse pool of resource types. Each type has a finite number of units, which get consumed ...
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82
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How to compute confidence interval xgboost regressor?
I have time series data to predict values for the next 6 months.
I have an xgboost model that predicts the six individual months, for the business what is important is that the cumulative value of ...
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34
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Uncertainty in stacked ensemble model
I am using the stacked generalization scheme to combine the predictions from different machine learning models (input models from now on).
I am currently calculating the prediction interval for each ...
- 111
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23
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Machine learning model that takes multiple records as input to help predict the last
I want to create a ML model that is able to forecast the yield from a farm. My data source gives me data about the inspections from the field, but that is too much info to fit in 1 record, so there ...
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input problems of using LSTM in python to forecast future value
There are two columns rainfall data and water level in my dataset and I want to predict the water level based of the past values using LSTM on python. My problem is do I need to include the past ...
