Questions tagged [machine-learning-model]
A machine learning model is a simplified representation of a dataset, derived from statistics in the data, used to make predictions. It can represent patterns, behaviours or features within this dataset which have been learnt by the algorithm during training.
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What would I prefer - an over-fitted model or a less accurate model?
Let's say we have two models trained. And let's say we are looking for good accuracy.
The first has an accuracy of 100% on training set and 84% on test set. Clearly over-fitted.
The second has an ...
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what kind of algorithm should I use to classify the text data example given?
What kind of classification or learning algorithm that suits this kind of data example
If I have to build a model using the given key words then predict column B and then to column A?
what kind of ...
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How can I choose the best machine learning algorithms from all kinds of algorithms?
When I want to find a model for my data set, I find that there are lots of algorithms that I can use. I know how to minimize selection choices by separating supervised and unsupervised algorithms and ...
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What happens when scikit-learn does a Lasso Model?
I have started an MLS course. As a beginner and non-mathematician it has been hard.
I am trying to understand the exercise about Lasso Models.
I have done Lasso models on R-cran, but this is my first ...
user70164
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What are the disadvantages of accuracy?
I have been reading about evaluating a model with accuracy only and I have found some disadvantages. Among them, I read that it equates all errors. How could this problem be solved? Maybe assigning ...
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LightGBM - Why Exclusive Feature Bundling (EFB)?
I'm currently studying GBDT and started reading LightGBM's research paper.
In section 4. they explain the Exclusive Feature Bundling algorithm, which aims at reducing the number of features by ...
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Encoding before vs after train test split?
Am new to ML and working on a dataset with lot of categorical variables with high cardinality.
I observed that in lot of tutorials for encoding like here, the encoding is applied after the train and ...
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Exploration in Q learning: Epsilon greedy vs Exploration function
I am trying to understand how to make sure that our agent explores the state space enough before exploiting what it knows. I am aware that we use epsilon-greedy approach with a decaying epsilon to ...
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How to chose a Machine Learning algorithm? [closed]
I was wondering, are their any guidelines or any rules of the thumb as to which algorithms perform best for each task?
What I'm looking for is something along the lines of:
NLP tasks are usually ...
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Dealing with categorical variables in regression problems which method to use?
Usually if I have regression problem and my initial dataset contains categorical variables like :
column 1:
Math
Science
Science
English
I would convert this ...
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Deciding on the number of components in PCA
I have been running my model several times now. Each time i get different results based on what number i put in my PCA component number range (I used raw numbers in the code instead of the range ...
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Why the VC dimension to this linear hypothesis equal to 3?
I am trying hard to understand this. Here is the scenario:
X = R^2
H = { h(x) = x + 10 }
I need to calculate the VC dimension for the above linear separator. ...
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Model to predict based on frequency of occurrence
I have the following dataset
+-----------------------------------+
| Passenger | Trip |
+-----------------------------------+
| John | London |
| Jack ...
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How to apply machine learning model to new dataset
I'm very new to machine learning & python in general and I'm trying to apply a Decision Tree Classifier to my dataset that I'm working on.
I would like to use this model to predict the outcome ...
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Which ML algorithm should I use for following use case for classification and Why?
I have data in table format having total 3 columns. One column for label, other two columns are features. So, such 30 rows(1 row contains 2 feature and 1 label) make one set of data with all 30 rows ...
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ML Project - Achieve 2 Objectives
I have a dataset with 5K records focused on binary classification. I am posting it here to seek your suggestions on project methodology
Currently what is my objective is
1) Run statsmodel logistic ...
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Refining AI problem statement - suggestions
I am looking for some guidance. My company is a electronic goods manufacturing company. We work with multiple distributors (around 7 distributors) across specific regions to sell our products. But ...
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Why best hyperparameters leads to drop in test performance?
I am working on a binary classification problem using random forests (75:25 - class proportion). Label 0 is minority class. So, I am following the below approach
a) execute RF with default ...
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Transform multi-class problem to multi-label problem
I found this question but I need an answer to the other direction.
Example:
Let's say we want to predict if a person with a certain profile wants to buy product A and/or B. So we have 2 binary classes ...
