Questions tagged [prediction]

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1answer
26 views

Why does MAE differ after prediction (Neural Network)?

I'm having trouble understanding what's happening in the following code. I already have defined x_train, y_train, x_val, y_val and x_test which define my training, validation and test sets. I'm using ...
2
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1answer
30 views

Using Majority Class to Predict Minority Class

Suppose I want to train a binary model in order to predict the probability of who will buy a personal loan and in the dataset only 5 percent of the examples are people who marked as bought a personal ...
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1answer
24 views

How to use random forest model to new data?

I am new to this Data Science field. I have a question to apply Random forest to new data. I have this table. ...
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0answers
22 views

prediction using LSTM

i have training data from 2015-2017 and testing data of 2018. i have multiple variables my data is multivariate time series data.i want to predict 2019 data by using test data of 2018.is it possible? ...
4
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1answer
24 views

Terminology - regression with one output and multiple output variables

I am trying to predict the response when the input is represented by Fourier transform. These form the features and are typically represented as a vector, $x_1,x_2,...,x_d$ where $d$ is the length of ...
2
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0answers
56 views

Making predictions in TensorFlow 2.0

I use TensorFlow/Keras on a daily basis to make predictions for a project. Everything works fine but I was getting regular warnings about the transition to TensorFlow 2.0 and I thought this week I ...
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0answers
20 views

Loss is decreasing but the predictions are not getting well

I am trying to implement a Dependency Parsing model using the transformer model in here with a few changes. On the training, my loss has decreasing trend; but the predictions at the end of 20 epochs ...
2
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1answer
20 views

Making predictions with missing numeric data

I don't know much about how to deal with missing data. When the data is categorical it doesn't seem too bad, if I one-hot encode it without dropping any of the actual categories, the missing data is ...
1
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1answer
32 views

How to forecast labels forward 3 years

I have many variables that I am using to predict median gross rent. I want to predict forward 3 years this is what my labels look like: How do I either preprocess the data in order to get a 3-year ...
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0answers
14 views

Prediction issue with xgboost custom loss

I have an issue with xgboost custom objectives: I do not manage to get consistent forecasts. In other words, the scale of my forecasts is not in line with the values I would like to predict. I tried ...
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0answers
14 views

Sales Prediction for multiple customers

In e-commerce, there will be lots of customers but each customer sales will be limited in number of records? In some cases, the records will be less 5 also. In cases like this, how to predict the ...
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0answers
24 views

Metrics for multi-class classification. When the prediction is of low quality

I am having a multi-class classification problem, so prediction of an instance to which class belongs to. I am reading that the typical metrics like accuracy or score are very "strict" on such ...
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0answers
22 views

Predict with some probability the day of the month paycheck received through daily transactions

I am using R to do machine learning. I have daily shopping expenditure data of individuals over a couple of months and my goal is to be able to identify through their shopping pattern the day of the ...
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1answer
38 views

Which Machine Learning methods would be good for a beginner-level Data Science project for described dataset? [closed]

I want to do my first beginner-level project regarding Data Science. I picked my data set which is described below. I want to make a Python script which will make some predictions on our data set ...
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1answer
15 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): ...
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0answers
68 views

Weather Forecasting: CNN-LSTM or ConvLSTM?

I am trying to develop a weather forecast model where satellite images (temperature, velocity field etc) are stacked over time. Since the prediction model needs to analyze both spatial features and ...
1
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1answer
53 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
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2answers
55 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
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0answers
58 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: ...
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0answers
34 views

Convolutional Neural Network for Structured Data

I am having a student dataset which is a record of student academic details I know that that CNN is mostly used in computer vision and image processing for analyzing visual imagery But here it is ...
0
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1answer
35 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: ...
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0answers
12 views

How to encode factor predictors in prediction models

The response variable as well as all predictor variables in my dataset are factors. I want to build a model for predicting the response variable. As I understand I have to first encode my predictor ...
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2answers
36 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 <...
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0answers
23 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
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1answer
170 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: ...
0
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1answer
20 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
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1answer
25 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 ...
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0answers
8 views

Derive main prediction for zero-one loss function

Intuitively I can see why mode of predictions is the main prediction of a zero-one loss function, but mathematically I am not sure how it is derived? Main prediction $= argmin_{y'}E_D[L(\widehat y, y'...
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0answers
8 views

pattern recognition tool

From what i've seen while searching google and the site this is most likely way simpler than what normally get's asked but i've not been able to find anything that could help me with it. What i'm ...
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0answers
8 views

SRGAN: How to adapt the model to the input image?

I wrote and trained my own SRGAN: so I obtained a generator’s model that takes 32x32 images as input and gives their improved 128x128 version as output… However, the end users of my Android app will ...
0
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1answer
21 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) ...
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0answers
16 views

Use sequential pattern mining rules to predict next window of a dataset

Suppose that I am performing Sequential Pattern Mining (maxgap = 1, i.e. rules for consecutive windows) and I ran the following code from arulesSequences in R Studio to determine significant rules ...
0
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1answer
17 views

Predicting complete time series for given parameter sets

Im 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 ...
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2answers
171 views
3
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2answers
148 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 ...
0
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1answer
13 views

nltk measure the accuracy of the new features

Have been playing around the NLTK algorithm for some data prediction. Starting form this gib, I started my understanding process. However, there are some bits that don't make sense. If I have a set ...
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3answers
40 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....
2
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1answer
27 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
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1answer
19 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% ...
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0answers
13 views

what are possible error analysis approach in tabular data?

I am working on binary classification on tabular data. The dataset is mostly made of categorical data and after fitting the data to a model I found test accuracy to be low. I want to do error analysis ...
0
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1answer
92 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
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2answers
108 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://...
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1answer
89 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
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1answer
87 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. ...
0
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0answers
9 views

prediction with un-obligatory features

I am pre-processing a real-world dataset with some features with missing values. these features are not mandatory - the user doesn't have to provide them. This means the values are not missing at ...
0
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0answers
24 views

Predicting house pricing given a dataset consisting of [ location: date of transaction: price ]

What would be the right way to tackle the problem of predicting median house pricing, given that the data I have for training consists in a big list of entries that have the following values: ...
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0answers
20 views

Modify image with machine learning

Here's my problem: I already have a little neural network that generate images using DCGAN, that was very entertaining to do but now I'd like to modify images using ML methods. Let me explain myself: ...
1
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1answer
862 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 model.predict() -> 1 This is happening for around 200 test values out of the test data of 10 lac. ...
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2answers
662 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 ...
2
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1answer
126 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 ...