Questions tagged [prediction]
prediction is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.
443 questions
5votes
1answer
28views
Wind Power Data Analysis - Python
I am seeking some help and or perspectives in solving a problem. I have a dataset (accessible here) with the following columns: DATE: this is the date in dd/mm/yyyy format HH: this is the "half-...
0votes
0answers
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using random forest to predict shipping rejection in various buckets (Final Disposition Activity Description) getting below error
ValueError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_34600/2721349307.py in ----> 1 model.fit(X_train,y_train) ~\Anaconda4\lib\site-packages\...
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3votes
0answers
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Predict the next status given previous sequence
I have a sequence dataset as the following. These sequences are statuses got approved by clients and they are ordered by date/time. A client can get multiple statuses and jump back to the same status ...
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Need Help Understanding AUC-ROC Curve
I am a student working on building a predictive model. While evaluating different models, I noticed that in some cases, some AUC is around 0.75, but the ROC curve appears below the random guess line. ...
2votes
0answers
53views
Prediction interval vs Confidence interval in a (Poisson) GLM (in Python)
In short, I get prediction interval smaller than confidence interval while they should be wider. Any help to understand why is certainly welcome :) Let me start by stating the problem at hand. I use a ...
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0votes
1answer
36views
Scaling and PCA for test data before prediction
I'm fairly new to the world of ML & Data Science. I've completed a certification course in Coursera/IBM and I'm trying to hone my skills using some exercises from Kaggle. The course did not ...
0votes
0answers
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What evaluation method is suitable if the detected data size is different from the actual (expected) one?
I want to evaluate the sequential tone detection system. Although the results are similar to what is expected, the problem is that the data size is different between the predicted data and the actual ...
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0answers
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Model Predicts Narrow Range of values but with promising MSE and RMSE values; ; Issues with Normalization and Error Metrics in Regression Task
I'm working on a spectrum sensing-based project, where I need to predict the SNR values from spectrogram images. To train and evaluate the model, I normalized the SNR ground truths, and I got decent ...
0votes
1answer
46views
Can Polynomial Features Be Used in Logistic Regression and Random Forest Models?
I am working in Python to predict the treatment response of 43 patients using 10 predictors as input. I noticed that adding polynomial features to my models produces nearly perfect results. I am ...
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Enhancing the predictive capability of traditional node-similarity indices with the Node2Vec algorithm
I am trying to test enhancing the prediction capabilities of traditional node-similarity algorithms, like the Jaccard Coefficient or Adamic Adar, with graph embeddings, like the Node2Vec. I think it ...
7votes
1answer
284views
When the regression models outperforms naive method?
I followed from this question. Case1: I have the following task to do: Training by the consecutive 3 days to predict the each 4th day. Each day data represents one CSV file which has dimension 24x25. ...
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0votes
1answer
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Multivariate linear regression via scikit and statsmodels
want to preface this first with terminology: multivariate regression deals with the case where there are more than one dependent variables while multiple regression deals with the case where there is ...
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1vote
0answers
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Need advice on feature engineering on Longitudinal Data
I'm trying to predict the rated capacity of a wind turbine given factors such as wind speed and direction. Now since this is weather data which is high resolution, I don't want to just average things ...
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0votes
1answer
48views
Daily Balance Prediction Using LSTM & ARIMA
I have the daily transaction history of a person from 1/1/2022 to 6/24/2024 in a csv file. The data is divided into train (1/1/2022 to 5/25/2024) and test (remaining). The data is given as : Date ...
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0votes
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Is it appropriate to utilize LSTMs for multivariate binary prediction on a timeseries by sliding block-by-block vs row-by-row?
I am trying to implement an ML algorithm for multivariate regression on a list of several timeseries. There are hundreds of timeseries, each one millions of rows long. There are 13 features, and I'm ...
