Questions tagged [decision]

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Combining DecisionTreeClassifiers

I have an array of sklearn.tree._classes.DecisionTreeClassifier classifiers that are used in a boosting algorithm, so the final classifier is a weighted sum of these individual trees. The problem is ...
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16 views

What is the purpose of pruning a decision tree?

What are the precise benefits of pruning a decision tree. What are the alternatives to pruning. When is it advantageous to do the alternative?
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21 views

Can you use a decision tree to predict a numeric variable? Is a decision tree that predicts a numerical variable a regression tree?

I am pretty sure that decision trees are only used to classify categorical variables. But I was wondering if there was a way for one to predict a numeric variable? If there is ... what is the method ...
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37 views

What is the relation between Linear Classifier and Linear Decission Boundary (or Non Linear Decision Boundary)?

As we know (Wikipedia Definition): Linear Classifier makes a classification decision based on the linear combination of the feature vectors. Mathematically : $y = f(\sum w_i x_i)$ So , $f$ is our ...
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13 views

Confidence Level for mean comparison among control and treatment group

I collected data where two players interacted with two choices each, where a 2x2 table resulted when representing the game in strategic form. The 4 outcomes are (A, A) ; (A, B) ; (B, A) ; (B, B). My ...
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1answer
24 views

decision tree classifier's square brackets

I am learning the decision tree classifier. The class here is whether or not a person will accept a loan offer (orange= not accept, blue=accept). I don't understand what do values inside the square ...
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43 views

Cost complexity pruning decision trees

I am trying to understand cost complexity pruning in classification trees. I found that DecisionTree in sklearn has a function called cost_complexity_pruning_path, which gives the effective alphas of ...
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1answer
31 views

Two question about a decision tree algorithm I found online

I am trying to learn decision trees but it has been difficult because the examples are extremely long and tedious and everybody seems to have a different algorithm in mind After some digging I found ...
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2answers
76 views

Identify the confidence of the impact of a proposed improvement initiative

Assume I have a manufacturing process that involves a moving train. It has failures of certain types like brakes and steering and also the weather. However, we can not do anything with regard to ...
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1answer
18 views

How do decision trees decide the value to be split upon for continous variables? [duplicate]

I know that decision trees make the split based on some metric such as entropy, information gain, gini index etc. But for continous variables how does it figure the value at which to make a split. For ...
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17 views

Classifier with the decision boundary y>f(x)

Imagine that I have data array $X_i$ (n-dimensional vectors) $Y_i$ (scalars) and classes for each point $C_i$(either zero or one). $i=1..N$ I am trying to train a binary classifier for this data ...
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22 views

Best approach to predict the days to wait to buy an airline ticket

I have a dataset with flight price observations collected over 3 months. I am trying to make a model that is able to recommend to a traveler the best time to buy a flight ticket, telling him the days ...
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10 views

How to choose the combination of factors that offer the best global response within a factorial design?

A factorial experiment was developed to find the influence of 3 factors in 2 response variables. The selected factors and their respective levels were: The chemical used Organic Inorganic The ...
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18 views

What is "categorical target variable" in SAS EM

"A categorical target variable that has exactly two categories (i.e., a binary or dichotomous variable)." What is "categorical target variable" in the SAS EM space? Is this ...
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24 views

Would I get optimistic results if I use random forest twice on my training set?

I have a data with 209k instances with 32 features and 3 unbalanced target labels (0,1,2). I am planning to apply Random Forest classifier since I also want to have insights about importance of the ...
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39 views

Are decision trees in SPSS classification or clustering trees?

I have a dataset consisting of 140 features (categorical and continuous variables) and one dependent variable (continuous). I used SPSS classify function without setting any classes, using CHAID ...
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1answer
31 views

How does a regression tree split the y variable

How does a regression tree split the y variable? Is it just a case of even chunking of the range or are the chunks of variable size?
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16 views

How to select the weights in a TOPSIS analysis?

In TOPSIS the sum of all weights needs to be 1 and that the selection of weights usually falls on the decision maker. At first it seemed to me that there was room for considering the weights as ...
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31 views

How to decide what is a "good move" or a "bad move" with supervised learning on a game?

Let's take an example game, like connect $4$, which is nice and simple. I know minimax is a super easy algorithm to program here, but let's say instead I wanted to create a Machine Learning model for ...
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1answer
64 views

Unbalanced dataset classification problem

I have a binary classification problem and I'm working with an unbalanced dataset. The count for each class in the training set looks like: ...
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1answer
82 views

What is the impact of a dummy variables to boosted trees?

I am currently reading the book "Random Forests" by Yu. L. Pavlov. Then it came across my mind the question If I were to use ensembled tree, say XGBOOST, do I need to transform each ...
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21 views

Is a "decision boundary" incompatible with proper scoring rules?

Having a decision boundary in a binary classification problem tells me that if the point lies on one side of the boundary, classify as $0$; if the point lies on the other side, classify as $1$. What ...
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76 views

How to convert continuous variable dataset into binary discrete values using Chi-Square testing for decision making

I have a dataset that contains continuous values for an attribute ranging from 0 - 100. I want to convert these continuous variables into two discreet values (say Label L1 and Label L2), So that the ...
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1answer
67 views

Overview of the main methods to prune decision trees

Could someone explain the main pruning techniques for decision trees. So something like the 3 most common techniques with a short explanation of how they work. I have looked online but this, ...
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1answer
45 views

Convert a categorical variable to a numerical variable for decision tree [closed]

I have a set of medical records, one of the columns has the name of 2000 different doctors. What do I need to do in order to convert these strings to numbers? I want to use a decision tree.
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1answer
396 views

Decision rule as a hyper-parameter in LASSO

I have a question that is related to the following: Is decision threshold a hyperparameter in logistic regression? but would like some clarification. The general consensus is that the decision rule ...
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1answer
48 views

can we use any learners in gradient boosting instead of trees?

As we are simply trying to predict residuals from weak learners and aggregating them, can we use any weak learners in gradient boosting machines instead of trees ? If so, why are the all the gbm ...
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1answer
127 views

Scikit's permuted features in decision tree implementation

In the Scikit's docummentation of decision trees I found a note: "The features are always randomly permuted at each split. Therefore, the best found split may vary, even with the same training data ...
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1answer
62 views

What does this ROC value mean?

What does this roc value mean? How do I interpret it? Are there values which help in inferring it like in case of kappa?
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1answer
180 views

Sucessive stimuli effect on auditive perception

My experiment is about auditive perception, and consists of playing sound at A Random locations (1-6), B Different frequencies (1-6), C is a Choice location (1-6 proposed choices). Participants were ...
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1answer
881 views

What to do if a specific parametric survival model does not converge but most other model do (implications for decision analysis)?

Please consider the following: In (health) decision modelling, an often-used approach is to extrapolate observed survival data with parametric functions. The NICE Technical Support Unit summarised ...
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1answer
473 views

Interpretation of regression tree with Poisson data

Above is a decision tree made by following code ...
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0answers
38 views

Determining the decision boundary for Naive Bayes

I'd like to know if this is a sensible idea and if there exist any already formed methods to do this (I'm new to the data science area). Essentially, I have used Naive Bayes to accurately classify ...
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2answers
776 views

Create a Complex Decision making AI (NEAT) from Scratch

I'm pretty new to the world of neural networks, so I'm asking this question, I'll explain in the process all the words used in the title so, if there's something unclear or wrong, I'll edit the ...
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1answer
16 views

Decision Tree on a set with reliabilty information

I've got an introductory AI course in my university, and I was taught about decision trees. I'm now facing a classification problem that seems solvable with a DT, but I'm stuck with an unseen ...
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152 views

Rpart and subsets

I am getting unexpected results from an rpart model, where the model selects two variables, one of which is a subset of the other. This in itself is not unexpected, but the seemingly odd thing is that ...
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1answer
61 views

Classification Tree or Regression Tree?

I have time series data: students that learned in groups for minimum 3 times and maximum 10 times and for each learning group session had to state if they faced a motivational OR a cognitive problem, ...
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1answer
70 views

Advertisment decision making based on customer past behaviour

Problem description: Every 3 weeks a fashion company sends out an expensive booklet with descriptions of clothes to each customer on their electronic records. There exists a purchase history what each ...
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0answers
156 views

Calculating Probability for Decision Tree Model

I came across calculation of probability for a decision tree model - which I do not understand. As I plan to do CEA of some health interventions I would not like to mess it up. The used method (...
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1answer
34 views

What is the optimal strategy to invest a limited resource in N uncertain options?

Suppose I have a £100 to invest in 2 options. Each option has a expected value, but the value is unknown. Option A has the highest average expected value, but a bigger uncertainty range. If we just ...
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2answers
161 views

Contributing predictors to a response variable

I have a dataset which has the following two tables which look like the following: ...
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1answer
45 views

SVM decision non linear

As I understand, to perform a decision in a non linear case (using a kernel) I use the following: $f(x) = sgn(\sum_{i=1}^{n} y_{i} \alpha_{i} \boldsymbol{k}(x,x_{i})+b)$ Where i=1,..n are the ...
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1answer
1k views
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24 views

Scaling weights in multi attribute decisions

I have a set of attributes that make up a feature (e.g 'Accommodation' in the sample below), each attribute has a weight range specific to the feature as per the picture. The intention is to have ...
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1answer
23k views

What is the difference between decision_function, predict_proba, and predict function for logistic regression problem?

I have been going through the sklearn documentation but I am not able to understand the purpose of these functions in the context of logistic regression. For ...
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1answer
136 views

Why adding new variables decreased the decision tree model's accuracy?

I am data modelling analyst in telecom company and now work on churn prediction model. I use decision tree algorithm with cross validation in SAS Enterprise Miner. The results are satisfactory as I ...
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1answer
193 views

Decision making under uncertaintly

In decision making under uncertainly we have these criterion 1- maximin criterion 2- minimax criterion 3- maximax criterion Now I want real life example to illustrate all of these criterion (I ...
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1answer
112 views

step by step explanation of answer for discriminant function [duplicate]

This is a question/answer from my first assignment (intro class on pattern recognition) I don't understand how they used the p(x given w1) and p(x given w2) in the discriminant function. For example, ...
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2answers
463 views

how do you combine the weak models in gradient boosted tree?

In this article https://www.analyticsvidhya.com/blog/2015/11/quick-introduction-boosting-algorithms-machine-learning/ The author indicates you combine 3 weak models into a final one using gradient ...
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1answer
63 views

What does a decision tree with both GOOD outcome means?

I have a decision tree built in R using rpart() from rpart package. However, when following the nodes, we have one condition leading to both outcomes as GOOD. This is weird for me. What does that ...