Linked Questions

0
votes
0answers
99 views

Why isn't accuracy of binary classification model improving? [duplicate]

I have a data set with a binary response variable, about 30,000 observations of 8 features, some are continuous and some are categorical. This is an imbalanced data set, the ratio of negatives to ...
0
votes
0answers
86 views

When to give up CNN? [duplicate]

i'm implementing my first CNN for image classification in a field with very few research. I'm aware i could extract feature and then try SVM, knn... But i want to be sure CNN is not a viable ...
0
votes
1answer
73 views

How to prove that special data is useless for given problem? [duplicate]

I have a dataset of sensor values and machine breakdowns. Based on the sensor values I try to build an early recognition of upcoming breakdowns (classic predictive maintenance task). I've been ...
0
votes
0answers
54 views

Accuracy of RNN getting stuck after 90% [duplicate]

I am using Keras RNN Cell to perform parts of speech tagging. The architecture is as follows(I cannot put the code because of privacy reasons) : An embedding layer of of 40 units of shape (...
5
votes
1answer
39 views

When to admit that your target cannot be predicted? [duplicate]

Assume you have a dataset, say churn. You sit down, do the data cleaning, the data engineering etc. etc. Since you want to predict if a customer churns, you decide on a logistic regression as a ...
1
vote
0answers
28 views

Why my machine learning's prediction appears to be random guesses? [duplicate]

I'm doing a classification exercise to predict churn using random forest. My current metrics are: Yes - Precision: 0.68 Recall: 0.61 No - Precision: 0.86 Recall: 0.9 However, whenever I try to ...
0
votes
0answers
26 views

Improving accuracy in time series forecasting [duplicate]

I am trying to forecast a very typical sales data. I have tried Arima, ETS, Holtwinters and even neural networks but I can't get a model with more than 40% accuracy [Absolute sum of(forecast-Actual)/...
0
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0answers
26 views

Acceptable Accuracy, Precision, Sensitivity, and Specificity Thresholds [duplicate]

Are there general rule of thumbs for acceptable accuracy, precision, sensitivity, and specificity values/thresholds in classification? I would imagine that this depends on different applications. I ...
0
votes
0answers
22 views

Small sample size with very skewed right response [duplicate]

I have a dataset of 300 observations with 7 predictor variables with 1 continuous response variable. The response is strongly skewed to the right and there are no significant correlations among any ...
0
votes
0answers
19 views

how to improve lasso regression model? [duplicate]

Im trying to build a linear model and accuracy in the model prediction is same for random set of features and a set of features - I believe should be associated with the variables. Is there anything ...
0
votes
0answers
18 views

when to give up in fitting a variable? [duplicate]

I would like to predict a variable from 5 features. I have bad scores (<50%) with all the algorithm I tried (Random Forest, Lasso, SGD, MLP). I would like to quantitatively assess if I should ...
0
votes
0answers
16 views

How to Improve the accuracy of my Cancer Prediction Model? [duplicate]

I'm building a logistic regression model to predict if a patient has cancer based on 9 features. Having built learning curves and increasing my regularization parameter to reduce over fitting, which ...
0
votes
0answers
14 views

Lack of accuracy for sales forecasting [duplicate]

I'm an intern in a company that sells about 900 products. We are trying to forecast our sales for the next year. I already have the monthly data for the 3 previous years, cleaned it, and analysed ...
0
votes
0answers
13 views

Lack of accuracy for my open market price forecasting [duplicate]

I'm trying to solve a problem to train my skill. I've daily data (each day during 10 years,2010 to 2020, except saturday and sunday). I would like to predict like ten day after my data end. Problem ...
57
votes
7answers
7k views

Industry vs Kaggle challenges. Is collecting more observations and having access to more variables more important than fancy modelling?

I'd hope the title is self explanatory. In Kaggle, most winners use stacking with sometimes hundreds of base models, to squeeze a few extra % of MSE, accuracy... In general, in your experience, how ...

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