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# Tag Info

### Is it possible to build ensemble models without a decision tree?

all the ensemble models I came through so far use/described using the decision tree. Random Forest is the "ensemble version" of decision trees. It's a commonly used ensemble method because ...
• 25.6k
Accepted

### What is the difference between horizontal and vertical ensemble?

I think the most highly-referenced source for these terms is Horizontal and Vertical Ensemble with Deep Representation for Classification (Xe, Xu, Chuang 2013). That would be the best place to get a ...
• 156

### Bagging vs pasting in ensemble learning

Let's say we have a set of 40 numbers from 1 to 40. We have to pick 4 subsets of 10 numbers. Case 1 - Bagging - We will pick the first number, put it back, and then pick the next. This makes all the ...
• 5,644
Accepted

### Can clustering my data first help me learn better classifiers?

It is absolutely a way to improve your classifier's accuracy. Actually a "strong" enough classifier such as a neural network could be able to learn by itself these clusters. However, you would need a ...

### Combining Classifiers with different Precision and Recall values

You want to ensemble your two algorithms. The way to do that is to not just use e.g. sklearn's precision and recall metric functions, but to actually obtain probabilities for being positive (most ...
• 171

### xgboost cannot identify perfectly fitting regression line

I think that the reason for this to happen is that tree-based methods have problems with linear problems. This is because tree-based methods do partitions of the variables, and not on combinations of ...
• 6,111
Accepted

1 vote

### Combining Classifiers with different Precision and Recall values

It seems like your goal is to improve the performance of your model using the outputs of two existing models with different strengths. The specifics of how you might want to combine these two models ...
• 11
1 vote

### When and how to use bagging?

Bagging main goal is to minimize variance of your model. Basically, if you have a model that is on average pretty accurate but inconsistent (meaning, it does well for a given data set, poorly ...
• 2,440
1 vote

### How to visualize Ensemble Models ( Random Forest) with 1000 estimators

You can try SHAP which visually explains the output of (many) machine learning model(s) including LightGBM and XGBoost. However, please note that it will not give you the entire Ensemble Model (Trees)...
1 vote

### xgboost cannot identify perfectly fitting regression line

(adding to what's said above by @David), The short answer is that, You can't expect the tree based models to Extrapolate... Had asked on Slack (quoting miguel_perez)and this was the reply, realize ...
• 2,470
1 vote

### Methods for ensembling ranked lists?

In this case, you might want to convert these into pair-wise relationships (e.g. item1 < item3), put together what you get from the different methods, and find a ranking which agrees with them the ...

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