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.

Filter by
Sorted by
Tagged with
1
vote
1answer
254 views

Why the first prediction of neural network in PyTorch is slower than following predictions?

So I have ResNet50 trained to classify images. For each prediction I track the time needed for it (input and model are moved to GPU): ...
1
vote
1answer
559 views

Machine learning in electrical circuit simulation [closed]

In the field of VLSI design, and specifically in digital circuits it is common to use electrical simulation software to find signal integrity issues. I would like to use machine learning instead of ...
2
votes
2answers
66 views

Incorrectly applying random forest model?

I am fairly new to random forest models (and data science in general), and was wondering if I am operationalizing the model I created correctly. Context: I am creating a random forest model to ...
2
votes
0answers
98 views

Results are too good.. what is wrong? How to predict correctly?

I am about to evaluate a neural network and want to check whether the predictions make sense. The variables: ...
0
votes
1answer
123 views

Feature engineering - house price prediction (small dataset) [closed]

I am working on the task of predicting real estate prices. My dataset has only 10 variables described below. I'm thinking about feature engineering but nothing comes to mind. Variables: ...
0
votes
2answers
116 views

Validate via predict() or via fit()?

There are several possibilites to evaluate a model: hist = model.fit(x_train, y_train, (...) validation_data=(x_test, y_test)) or to use <...
1
vote
0answers
45 views

How to deal with similar feature values but each indicates to a different information?

If I have a feature with replicated values but each of these values indicates a different piece of information. example: feature 'street name' with value 'A' which some of these 'A's are for Boston ...
0
votes
1answer
3k views

clarification on train, test and val and how to use/implement it

So far I think I understood the differences between the training, test and validation set. Basically it is like in this image: Training set: The data where the model is trained on Validation set: ...
1
vote
1answer
29 views

Why is my prediction using ARIMA better if I'm using less historic data?

I have a data set containing hourly electricity prices for since 1.01.19 until September. Since the process turned out to be (weakly) stationary, I applied an ARIMA model in Python in order to predict ...
2
votes
1answer
35 views

Neural Network Multiple | Averging predictions

I am training multiple neural networks with various parameters. I am trying to average their predictions, but I am not really sure what that means, I am confused about what to average exactly. Here is ...
1
vote
1answer
70 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
votes
1answer
26 views

Predicting complete time series for given parameter sets

I am searching for an approach that is able to predict a complete time series for a given parameter set. Imagine a robotic arm which has a starting position and a target position. There is a sensor ...
0
votes
2answers
2k views
5
votes
2answers
2k views

Is There a Way to Re-Calibrate Predicted Probabilities After Using Class Weights?

I have classification data with far more negative instances than positive instances. I have used class weights in my models and have achieved the discrimination I want but the predicted probabilities ...
1
vote
1answer
19 views

nltk measure the accuracy of the new features

I have been playing around the NLTK algorithm for some data prediction. Starting from this gib, I started my understanding process. However, there are some bits that don't make sense. If I have a ...
0
votes
3answers
60 views

Predict the salaries of customers in 2019 from 2016 data

I have a spreadsheet of data with ages and salaries for 2016. For example, in 2016 there were 12988 customers who were 18 years old and earned 20k. I need to predict the salaries of customers for 2019....
3
votes
1answer
33 views

Predicting probability for each tag given already chosen tags

I have a set of tags (~10'000, will be extended over time) presented to a user. After he has selected 3 or more tags, I want to predict for each remaining tag what the chances are that the user will ...
1
vote
1answer
26 views

Finding the usage percent to perform predictive analysis for new users

Problem Statement- I have to find the average feature usage all the users and the usage of user X to suggest if he should use the feature. Example - On google home page out of all the user's avg 85% ...
1
vote
1answer
337 views

Decision tree classifier prediction changes from one run of the model to the next

I'm running a very basic gender ['male', 'female'] classifier using the sklearn DecisionTreeClassifier based on ...
1
vote
2answers
578 views

Splitting training and test set with financial data

I am using trees algorithms (decision tree, random forest and XGBoost) to forecast the sign of the returns in the stock market (classification). I am using this article as a reference: http://...
1
vote
1answer
373 views

Multivariate time series prediction with binary target

I have an electronic component whose sensors record temperature, current and voltage values of various sub-elements. These readings are taken at regular intervals of time and I organized them as ...
1
vote
1answer
131 views

How to predict whether the client will renew the subscription or not based on given data structure

I have a requirement where I want to predict whether the client will renew the subscription or not. And the data is something like below. Basically client's subscription end date can be anything. And ...
1
vote
1answer
8k views

XGBOOST : model.predict_proba() and model.predict() conflicting behaviour

I have two classes 1 and 2: The output of model.predict_proba(): [0.333,0.6667] The output of ...
2
votes
2answers
4k views

Prediction after one hot encoding

I have a regression model that I want to make prediction based on values that I will get from an end user. In my dataset, I have one categorical variable region ...
3
votes
1answer
227 views

How to deploy ML models in production?

Have been learning Machine Learning concepts and doing hands-on past few months. Now got a bit different doubt than implementation of code. This is regarding measures to be considered while ...
0
votes
1answer
26 views

Identifying importance of each feature in deep model

I have a deep model and I want to figure out which feature has the maximum influence on predicted result. For this I train the model with all the features I think are important, during prediction I ...
0
votes
1answer
229 views

Machine Learning based Multivariate Time Series Prediction - How to create supervised data format

Q1: I have a multivariate time series dataset. For each timestep, there are 11 features and 1 output. I am going to use supervised ML to predect the output. I understand that in univariate cases, if ...
0
votes
0answers
14 views

Find possible fearure values to predict a certain outcome

I have a dataset about patients waiting times in a health district. The data is aggregated by health provider, type of medical procedure, urgency of the procedure (3 classes) and reports the n. of ...
0
votes
1answer
302 views

Include time as a variable in regression model

I am currently working on a regression problem which requires me to predict the costs of a fixed asset. I have used several variables to do so and derived a predicted cost. However, my superior has ...
2
votes
1answer
28 views

How can I get an algorithm to have an evalutation metric based on aggregate predictions?

Let's say I have a model that makes a prediction per individual. An example data set is below. Normally, evaluation metrics (for example within the XGBoost algorthim), are used at the individual ...
0
votes
1answer
45 views

LSTM get next output with Keras

So I'm learning RNN, and tried to do a prediction LSTM, but I do not understand how the output works. I have this LSTM RNN: ...
0
votes
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 ...
2
votes
1answer
1k views

Xgboost multiple class predictive performance beats one versus rest

I have an NLP task I'm tackling with xgboost (R implementation). Before describing my doubt I'll give you some background: I have a corpus of documents for which I did topic discovery, using a term ...
1
vote
1answer
51 views

Predicting when component will fail having its parameters data

I have a component and I need to predict when it will wear out and will need replacement. I monitor, let's say 5 parameters of this component, each one is monitored for every run cycle. So, the ...
2
votes
2answers
72 views

Sequence prediction with unlimited predictions

I have a special kind of prediction problem. I have observed $M$ sequences $X_m = [x_1, x_2, ..., x_N]$ where the distance $d$ between $x_n$ and $x_{n+1}$ is drawn from the same normal distribution, ...
0
votes
1answer
49 views

Why am a getting wrong prediction when combining two list of samples, which individually gives correct prediction?

So I am coding in Python. I have to set of samples. Set1 contains samples of class A and the other set, Set2 contains samples of class B. These samples taken are a part of the training dataset. When I ...
3
votes
0answers
47 views

Timeseries prediction error measurement. How to deal with diffrent time scales?

I have some time series and a prediction model. Now I would like to measure how good/bad the prediction is for different products. The problem is that for each product the time points (frequency of ...
0
votes
2answers
189 views

How can i test the performance of a model when the test data contains seen and unseen data

To test the performance of my model based on some selected features, i try to use unseen and seen data. However, when choosing the accuracy based on all data, the model is almost overfitting since ...
3
votes
3answers
734 views

When is it convenient dropping duplicates when performing Time Series Prediction?

I have this Dataset. ...
1
vote
1answer
45 views

What could make a set of the train data more predictive than the whole train data

I took a sample of my training data and balanced it and then trained my model. The results obtained are more accurate than using the whole set of train data (balanced or imbalanced). My question is: ...
1
vote
0answers
22 views

Multi-label learning, how to interpret the scores of instances

I am working on a multi-label learning classification problem. When I tune the hyperparameters of the model, the sign of each label (each line on the MLL) remains the same while the scores change. ...
1
vote
2answers
6k views

ValueError: Expected 2D array, got scalar array instead using predict method

I am trying to get a predicted value instead of whole features for a particular level using predict method. ...
0
votes
0answers
47 views

Choosing loss function in Keras for prediction binary_crossentropy or categorical_crossentropy

What loss function in keras should I chose for binary_crossentropy or categorical_crossentropy? I have data like : $w1,w2,w3,w2,w2,w1,w3,w5,w9,w5,w4...$ I want to predict sequence: input: $w1,w2,w3$...
0
votes
1answer
46 views

Searching prediction from 4 datasets

The fourth dataset contains (train_data, test_data, previous_data, and information_history_data). The goal is to search for a user's rating on the loan to the bank. ...
0
votes
1answer
410 views

Best metric in imbalanced classification for multi-label classification

My test data are imbalanced, i tried to use the precision or the gmean as metrics for a multi-label learning model, but both metrics are not very informative. Is there any way to use for example the ...
0
votes
0answers
119 views

How can I evaluate my sequence prediction model?

I want to evaluate the performance of my prediction model , which is an VED (Variational Encoder Decoder) used for sequences prediction (it predicts the next sequence knowing the actual) I want to ...
0
votes
1answer
142 views

Adding hour data to Date feature in time series prediction

I'm a noobie with regards to working with time series data. I have a time series data which has date column in YYYY-MM-DD and a hour column containing 0 to 23 representing hour of the day and the ...
1
vote
2answers
3k views

difference betwen predicting seen and unseen data

I tried to test my model with seen and unseen data (seen data are data that i used to learn the model). I figure out that as much as i increase the number of features seen data can be properly ...
0
votes
2answers
46 views

Statistical methods for Sequence learning

I am bit more traditional and I am looking for a statistical method that can help me also do inference or predictions. I have some table that contains some transitions, where each row of the table ...
0
votes
3answers
584 views

What is the minimum amount of data required for sales prediction with ML

I have historical data from the MySQL DB which contains 33 months of data. The features in the data are state, depot, product type, purchase date, salesperson name, volume, and price. Using this ...

1 2 3
4
5
8