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H: Variable Importance Random Forest on R
I am currently using a random forest model for classification, however I am unsure how the feature selection technique "varImp" works on R. I understand the context of variable importance, however when I implement it in R it doesn't seem to produce the results I expect.
When ... |
H: The Why Behind Sum of Squared Errors in a Linear Regression
I'm just starting to learn about linear regressions and was wondering why it is that we opt to minimize the sum of squared errors. I understand the squaring helps us balance positive and negative individual errors (so say e1 = -2 and e2 = 4, we'd consider ... |
H: Why do so many functions used in data science have derivatives of the form f(x)*(1-f(x))?
The sigmoid function's derivative is of that form, and so is the softmax function's. Is this by design, or some strange coincidence that seems to work for ML models/neural networks?
AI: Sigmoid function is a partial case of so... |
H: Structure of Convolutional Neural Network to analyze a sequence of frames
I want to apply a CNN to a series of image sequences to classify that sequences of frames/images in two groups/categories. We are in a binary classification problem. My dataset is composed by a lot of 'batches' of frames. For example, each ba... |
H: Can clustering my data first help me learn better classifiers?
I was thinking about this lately. Let's say that we have a very complex space, which makes it hard to learn a classifier that can efficiently split it. But what if this very complex space is actually made up of a bunch of "simple" subspaces. By simple, ... |
H: Dimension of weight matrix in neural network
Why would the dimension of $w^{[2]}$ be $(n^{[2]}, n^{[1]})$ ?
This is a simple linear equation, $z^{[n]}= W^{[n]}a^{[n-1]} + b^{[n]}$
There seems to be an error in the screenshot.
the weight, $W$ should be transposed, please correct me if I am wrong.
$W^{[2]}$ are the w... |
H: Time Resolution Changes in Time Series Forecasting
I am doing time series forecasting for estimating monthly sales of certain consumer goods SKU.
I have last 3 years of actual sales data, wherein first 2.5 years of data is monthly sales data, but last 6 months data daily sales data is available.
I can certainly ad... |
H: Does Non Negativity Constrains increases the estimation error
I have been working with Tensor and matrix Non negative constrained algorithms. I have never seen a non negative constrained algorithm (ex. Non Negative Tucker Decomposition NTD) with error that is comparable to the non constrained algorithm (ex.High Ord... |
H: Confused by kmeans results
I am using kmeans to cluster some data with 2 features. Not sure I understand why kmeans is producing the clusters I see:
Why would kmeans not cluster these points in a way that matches what we would expect visually looking at the data? Why are seemingly random points in the middle of vi... |
H: Non Scaled New Actual Data
I am new to Machine Learning and I have a conceptual question.
I have a scaled dataset (scikit-learn and pandas).
After training/testing my algo, I will make new predictions using new actual data which will not be scaled or normalized.
Will this discrepancy be a problem, if so, how should... |
H: Is Java or Python a better choice for an application involving data intensive algorithms employing natural language processing?
I am a professional java developer with 9 years of experience. Never worked with Python but, I do not have any restraints learning it.
Still I need clarity on a couple of aspects. I hope i... |
H: How to prevent a neural network from choosing the 'easiest' solution
I have a neural network that takes in roughly twelve values, and outputs a singly probability. The issue is that the network appears to be smart enough to realize there is a very significant correlation between three of the values and the output, ... |
H: Why ReLU is better than the other activation functions
Here the answer refers to vanishing and exploding gradients that has been in sigmoid-like activation functions but, I guess, Relu has a disadvantage and it is its expected value. there is no limitation for the output of the Relu and so its expected value is not... |
H: Classifying job titles
I have a dataset of about 10000 unlabeled job titles (mostly very short titles) such as head of mobile or lead iOS developer.
I would like to perform classification of those job titles in two different ways :
The 1st classification is sorting job titles according to the type of job it repres... |
H: Need help understanding the structure of this convoluted neural network
I'm trying to grasp the structure of this convoluted neural network.
(Source)
I understand the first layer is a 6x6 conv with stride 2 followed by 3x3 max pool and then 6 5x5 convs and another 3x3 max pool. After this, however, outputs from a ... |
H: Does Kernels always map data points to higher dimensions
When we use kernels in SVM to linearly sperate non linear data points by mapping it to 'another dimensions', does this suitable 'another dimensions' always be a higher dimension with respect to original dimension of the data points?
And is it true that we can... |
H: Using dates from predicting loan
My goal is:
Calculate the probability of a client take a loan.
My problem is:
How to take in account the date of the loan in this process.
Certainly the date is important here since, let's assume my clients usually take loans closer to Christmas, for example.
My initial thought was ... |
H: How to decide which images to label next?
We have a custom dataset of 20 thousand images with two pixel-wise labeled classes.
However we have 1 million more raw images, which we would like to label.
We want to label the most important new images first. Importance is defined as:
Images with the more new informatio... |
H: Proper derivation of dz[1] expression for backpropagation algorithm
For backpropagation algorithm, is it true to have weight, $w$ transposed in the expression of $dz^{[1]} = w^{[2]T}dz^{[2]} * g^{[1]'}(z^{[1]}) $ ? Could anyone show me why $w^{[2]T}$ instead of just $w$ ?
I have read other articles, but the transpo... |
H: Decision Tree Classifier with Majority vote (Is 50% a majority vote)
I have a homework question that requires me to create a 3 level tree (root, intermediate and leaf) with majority vote and expand the tree if 3 level tree is not possible. I have to use ID3 algorithm. Its a manual question rather than coding assign... |
H: Difference between RFE and SelectFromModel in Scikit-Learn
What is the difference between Recursive Feature Elimination (RFE) function and SelectFromModel in Scikit-Learn? Both seems exactly similar.
AI: They effectively try to achieve the same result but the methodology used by each technique varies a little.
RFE... |
H: Should I relabel this data or remove the potentially leaky feature?
Putting together a Keras MLP to predict whether a value will exceed a static percent threshold in the next 15 minutes. The incoming data is a rolling percentage which moves smoothly for the most part because the data comes in every few milliseconds... |
H: In R, can I integrate different classifying algorithms in one bagging model?
I use R to do data analysis. I have a dataset. When I use different classifying algorithms, such as random forest, SVM, etc, I have the different accuracy. So, I want to integrate all the algorithms into one framework, let's say adaboost. ... |
H: How to add time as a feature into clustering algorithm?
I've wrote here about my problem. And now I have a new one.
How to use time as a feature? I have a pandas DataFrame with date-time column('date') and I don't know how to use it as a feature. For now I'm using TfidfVectorizer.
from sklearn.feature_extraction.t... |
H: Charts with or without grids?
I am writing a thesis and don't know if the charts below should have grid lines or not. Do they need the grid lines?
An example without the grid lines:
AI: I would say that it is really up to you here. I don't think that the grid lines are distracting in any way, but can be helpful i... |
H: Where can I find a trained neural network data to play with?
This is the trained neural network for the XOR operator:
Can I find something like a trained network for recognizing hand writing digits somewhere on the internet? Is there an "official format" for trained neural networks?
AI: What about the super popula... |
H: What are the advantages or disadvantages of Owl?
Owl is the numerical library for OCaml: https://github.com/ryanrhymes/owl
It is supposed to be an equivalent of numpy and also have capabilities of tensorflow.
Any insights on why it should be used or why it shouldn't?
AI: In a nutshell it is promising but it lacks i... |
H: Sklearn Aggregating Multiple Fitted Models Into A Single Model? (binary classification)
My problem context:
dataset too big to fit into memory.
binary classification [0,1]
30 csv files in a directory with exactly 30,000 samples (rows)
each file contains 15,000 0 class and 15,000 1 class (no unbalance)
model is xgb... |
H: What is the best way to classify data not belonging to set of classes?
I am building a multi-class support vector machine (8 classes to be precise) on an image dataset of pre-defined classes. And then I thought of a question:
What if I have an image that doesn't belong to the set of predefined classes, what would ... |
H: What is PAC learning?
I have seen here but I really cannot realize that.
In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions. The goal is that, with high probability (the "probably" part), the selected function... |
H: What are real world applications of Doc2Vec?
I am new to Doc2Vec. As I understand Doc2Vec group similar documents based on the context of their words.
I have a set of newspaper documents and I want to identify what are the main topics of the newspapers (group 'Politics' news documents to one group, 'Sports' news do... |
H: Interpretation of probabilities from logistic regression in Credit Score Card modelling
I was trying to understand the probabilities output by a logistic regression in credit scorecard, let us say that I have performed Vintage analysis and identified the performance period as 6 months , and Bad rate is defined as 9... |
H: Reporting test result for cross-validation with Neural Network
I have a small dataset, so I have to use cross validation to report the test result to get a better estimate of the classification result. For some reason, I have to use neural networks to do this.
Because neural networks have their unique quirks e.g fi... |
H: What machine learning technique should I use in medical problem
What are the best machine learning techniques to classify responders to a medicine if I have:
Clinical data with ~200 features (age, education, marital status etc.)
Gene data with around 250K features (genom data (snips) taken from the patient (DNA an... |
H: Converting Json file to Dataframe Python
I have a json file which has multiple events, each event starts with EventVersion Key. The data looks similar to the following synthesized data.
{"Records":[{"eventVersion":"1.04","userIdentity":{"type":"R","principalId":"P:i","arn":"arn:aws:sts::5","accountId":"50","accessK... |
H: How many features to sample using Random Forests
The Wikipedia page which quotes "The Elements of Statistical Learning" says:
Typically, for a classification problem with $p$ features, $\lfloor \sqrt{p}\rfloor$ features are used in each split.
I understand that this is a fairly good educated guess and it was pro... |
H: What does discriminator of a GAN should do?
A Generative Adversarial Network (GAN) consists of two sub-networks: (1) generator and (2) discriminator.
What does a discriminator should be able to do? Or more specifically, should it be able to distinguish (classify) a real object (for example a vector) from a generate... |
H: Fractions or probabilities as training labels
This it a problem that has come on my path a few times now and I don't have a satisfying solution yet. The goal is to predict probabilities or fractions based on some $x$ where our training $y$ has these probabilties or fractions and thus is in the domain $[0,1]$ as opp... |
H: Can we use machine learning to generate a text output based on the input strings
Problem : Generate a text output based on input strings which will be combined using a number of rules.
Example :
Feature1 Feature2 O/P
Rule 1 Enum_Domain Priority /Enum_Domain/... |
H: Forecasting one time series with missing data with help of other time series
I have time series $R$, which shows, how something changes at the regional level.
I have several time series $U_i$, which show, how something changes at a special unit $I$ level.
There are many units in the region. $R$ has no missing data.... |
H: Is the percepetron algorithm's convergence dependent on the linearity of the data?
Does the fact that I have linearly separable data or not impact the convergence of the perceptron algorithm?
Is it always gonna converge if the data is linearly separable and not if it is not ? Is there a general rule ?
AI: Yes, the ... |
H: Keras autoencoder not converging
Could someone please explain to me why the autoencoder is not converging? To me the results of the two networks below should be the same. However, the autoencoder below is not converging, whereas, the network beneath it is.
autoencoder implementation, does not converge
autoencoder =... |
H: Loss of MSE always be 0 when keras for topic predict
my input is a 200 dims vector, which is generated by mean of the word2vector of all words of a article, my output is a 50 dims vector,which is generated by the LDA results of a article I want to use mse as the loss function,but the value of the loss always be 0 m... |
H: Why are autoencoders for dimension reduction symmetrical?
I'm not an expert in autoencoders or neural networks by any means, so forgive me if this is a silly question.
For the purpose of dimension reduction or visualizing clusters in high dimensional data, we can use an autoencoder to create a (lossy) 2 dimensiona... |
H: Breaking captcha with a neural network - Learning deep learning
I would like to implement a neural network allow to make captcha recognition. Actually, I'm new in deep learning that's the first neural network I'm building.
I have seen a another similar project on Github : https://deepmlblog.wordpress.com/2016/01/0... |
H: What are differentiable modules used in deep learning
I am reading this paper.
Convolutional Neural Networks define an exceptionally powerful class of models,
but are still limited by the lack of ability to be spatially invariant to the input data
in a computationally and parameter efficient manner. In this w... |
H: Median versus Average, how to choose?
I want to test how long it takes to run an algorithm.
So here is what I am doing:
close all the other un-needed applications, run my algorithms alone
considering some unstable computer system factors, run multiple times
As you can tell, I can get a set of running time t1, t2,... |
H: Should I gray scale the image?
I'm categorizing 30 types of clothes from the image using R-CNN Object Detection Library from tensorflow : https://github.com/tensorflow/models/tree/master/research/object_detection
Does color matter when we collect images for training and testing?
If I put only purple and blue shirt... |
H: Using machine learning to evaluate a random number generator
Let's say that I want to create a pseudorandom number generator, and I'd like to make sure that it's truly close to random. For simplicity, let's assume that I want to output a 0 or a 1 randomly.
I have heard of the monobit, runs, poker test etc. but are ... |
H: Tensorflow MLP worse than Keras(TF backend)
I'm kinda new to this field, so I started tinkering with some models in Keras (using Tensorflow backend). But recently I started to migrate to a pure Tensorflow approach, and I'm not getting good results, what is strange, since I'm using the TF backend in Keras, so I was ... |
H: K-mode or K-prototype
I'm studying about K-mode and K-prototype but I cannot find any proper example on a very basic example of how it works contrary to K-means where there are quite a lot (like this one description-k-means).
Does anyone know a book or website which have a similar example for K-mode and/or K-protot... |
H: How to implement gradient descent for a tanh() activation function for a single layer perceptron?
I am required to implement a simple perceptron based neural network for an image classification task, with a binary output and a single layer, however I am having difficulties. I have a few problems:
I am required to ... |
H: Why do we need XGBoost and Random Forest?
I wasn't clear on couple of concepts:
XGBoost converts weak learners to strong learners. What's the advantage of doing this ? Combining many weak learners instead of just using a single tree ?
Random Forest uses various sample from tree to create a tree. What's the advant... |
H: Deep Learning to estimate what is beyond the edge
I have an image of some data which is approximately 4,000 x 8,000 pixels. I am interested in finding out if anyone has used a deep learning algorithm to predict what would be on the image if it extended 100 more pixels in each direction. I would imagine that the d... |
H: How can I deal with circular features like hours?
Assume I want to predict if I'm fit in the morning. One feature is the last time I was online. Now this feature is tricky: If I take the hour, then a classifier might have a difficult time with it because 23 is numerically closer to 20 than to 0, but actually the ti... |
H: LDA vs Word2Vec vs Others for predicting recipients of a message
I'm investigating various NLP algorithms and tools to solve the following problem; NLP newbie here, so pardon my question if it's too basic.
Let's say, I have a messaging app where users can send text messages to one or more people. When the user type... |
H: Is there a model-agnostic way to determine feature importance?
Sklearn has a feature_importances_ attribute, but this is highly model-specific and I'm not sure how to interpret it as removing the most important feature does not necessarily decrease the models quality most.
Is there a model-agnostic way to tell whic... |
H: What are some good papers that discuss Tufte's 'data density index' and 'data-to-ink ratio' in data visualisation?
I've found a number of resources that mention Tufte's 'data density index' and 'data-to-ink ratio' when considering the analysis of particular visualisations and visualisation techniques, but I am yet ... |
H: Understand clearly the figure: Illustration of a Convolutional Neural Network (CNN) architecture for sentence classification
I am studying the blog: Understanding Convolutional Neural Networks for NLP. It is very good blog.
One thing I can't understand clearly about this blog. As the figure Illustration of a Convo... |
H: Sentence similarity prediction
I'm looking to solve the following problem: I have a set of sentences as my dataset, and I want to be able to type a new sentence, and find the sentence that the new one is the most similar to in the dataset. An example would look like:
New sentence: "I opened a new mailbox"
Predictio... |
H: How do I represent SURF Features into Bag of Words to determine Nearest Neighbors?
I'm trying to use Speeded Up Robust Features (SURF) to get the $k$ most similar images from a set of images in my directory. I'm planning to use $k$-Nearest Neighbours ($k$-NN) for this. As far as I know, the size of SURF descriptors... |
H: Forgetting curve using Duolingo data
I'm trying to replicate the forgetting curve using the open sourced Duolingo data for fun.
The problem is that my finding doesn't make any sense, namely that the longer you wait the better recall value. Anyone have any pointers?
# make our plot outputs appear and be stored withi... |
H: Match an image from a set of images : Combine traditional Computer vision + Deep Learning/CNN
In the application I am developing, I have about 5000 product label images.(One label per product).
One functionality of my application is that user can take a picture using his camera and get a possible match(es) against ... |
H: Random Forest Classifier gives very high accuracy on test set - overfitting?
I have a financial dataset, where I'm trying to predict company types, based on the amount dollars, what time of day, and whether they buy or sell (currency pairs). It looks like this:
The features I use to predict:
X.head():
Dollars | ... |
H: Amount of multiplications in a neural network model
I'm currently reading this book and want someone to tell me if what currently I'm assuming about neural network is right or not. https://www.pyimagesearch.com/deep-learning-computer-vision-python-book/
If a layer has 30 neurons: In a feedforward meural network ... |
H: What are graph embedding?
I recently came across graph embedding such as DeepWalk and LINE. However, I still do not have a clear idea as what is meant by graph embeddings and when to use it (applications)? Any suggestions are welcome!
AI: Graph embedding learns a mapping from a network to a vector space, while pres... |
H: Input for Sales Forecasting
I want perform demand forecast for particular item based on attributes.Did I need to train the model with unsold items ? by maintaining sales Quantity as zero or go with only items sold in training period.
AI: In short, if there is supply, it should be in the model to determine demand:
... |
H: Is it possible to plan and assign Data Science tasks by complexity levels based on team members' experience?
How would you assign Data Science primary tasks to Data Scientists in a team according to a colleague' seniority? I mean, as always you can expect different things and also level and pace of self-learning.
F... |
H: How to clone Python working environment on another machine?
I developed a machine learning model with Python (Anaconda + Flask) on my workstation and all goes well. Later, I tried to ship this program onto another machine where of course I tried to set up the same environment, but the program fails to run. I copied... |
H: Can we implement random forest using fitctree in matlab?
There is a function call TreeBagger that can implement random forest. However, if we use this function, we have no control on each individual tree. Can we use the MATLAB function fitctree, which build a decision tree, to implement random forest? Thanks a lot.... |
H: Converting a nominal attributes to numerical ones in data set
I'm using the NSL-KDD data set which contains nominal and numerical values, and I want to convert all the nominal values to numerical ones. I tried the get_dummies method in python and the NominalToBinary method in WEKA, but the problem is that some nomi... |
H: How to preprocess data?
What is the generic way to preprocess data for machine learning and predictive models ?What are the sequence of steps to be taken?
AI: You are having a dataset with both continous and categorical data
1.Centre the data
for numerical variable
centering usually done by subtracting mean of the ... |
H: what are the top level subsets/domains of ML?
I'm not really happy with the mind maps I've been able to find on Google, most of them are algorithm based. I want to make a good one that is problem/solution domain based. Do I have this right for my top level nodes? Here is the general direction I am headed: https:... |
H: Multiple time-series predictions with Random Forests (in Python)
I am interested in time-series forecasting with RandomForest. The basic approach is to use a rolling window and use the data points within the window as features for the RandomForest regression, where we regress the next values after the window on the... |
H: Which regularizer to use to get a sparse set of regression parameters?
I am doing a regression and I want to use the regularizer that will be the most useful to get a sparse set of parameters.
Which regularizer should I use ? Cardinality? maximum value ? Sum of absolute values ? Euclidean norm ?
AI: The most common... |
H: Cropping Images for Dataset
Problem
I want to train HyperGAN with a set of 400+ images of people, but they aren't the specified size (32x32 pixels) for training.
Question
Is there any way/program to help cropping/resizing them so as to not do it 100% manually?
AI: Cropping and/or resizing is very trivial using Open... |
H: How to treat sparse categorical features in a Neural Network for multiclass classification with Tensorflow?
I am building a Neural Network for multiclass classification.
My dataset has 3 millions of observations. My features are 7 unordered categorical values. My problem is sparse as 4 features among the 7 can take... |
H: Text annotating process, quality vs quantity?
I have a question regarding annotating text data for classification.
Assume we have ten volunteers who are about to annotate a large number of texts into label A or B. They probably won't have time to go through all the text samples, but at least a significant portion o... |
H: Forecasting: How Decision Tree work?
For example I have the following data structure:
user: Chris
age: 32
income: 60.000
basket value: 45
I want predict the basket value, and my features are the age and income.
With a linear regression I get a regression function as the result of the fitting for example: $$y = 0.5... |
H: Why should I normalize also the output data?
I'm new to data science and Neural Networks in general.
Looking around, many people say it is better to normalize the data before doing anything with the NN. I understand how normalizing the input data can be useful.
However, I really don't see how normalizing the output... |
H: The automatic construction of new features from raw data
Some observations are far too voluminous in their raw state to be modeled by predictive modeling algorithms directly.
Common examples include image, audio, and textual data, but could just as easily include tabular data with millions of attributes.
Feature ex... |
H: Regression: Should "known outputs" be also activated?
Okay so, I understand that inputs are sent directly to the network (basically being multiplied to weights of the nodes, receive a bias, and gets activated) and then the network produces an output through this feed forward method.
Now, in order for the network to... |
H: How would you optimize this code?
I have the following code written using the pandas library. I would like to know if there are ways to optimize the code.
for column in df:
for index, row in df[column].iteritems():
if type(row) == str:
if 'R$' in row:
n = row.replace('R$', '')
n... |
H: Word2vec continuous bag of words and skip grams model
Recently, I want to understand word2vec.
I know there are two algorithm behind word2vec.
One is CBOW another is Skip grams model.
Here is question, is CBOW also have windows size like skip-gram model and will do iteration of corpus?
For example, "I am eating piz... |
H: Does the choice of normalization change dramatically the result of a KMeans
I'm using a KMeans to get the profile of several users according to several columns (I'm working with RStudio).
To analyze my clusters, I decided to realize a radar chart, so I decided to use feature scaling : x-min(x)/diff(range(x)), to ha... |
H: Logistic Regression : Solving the cross-entropy cost function analytically
Logistic regression cost function is cross-entropy. It is defined as below:
This is a convex function. To reach the minimum, scikit-learn provides multiple types of solvers such as : ‘liblinear’ library, ‘newton-cg’, ‘sag’ and ‘lbfgs’.
Is... |
H: Multiple Object recognition in image using deep Learning
I am working on recognizing object classes in images using neuronal nets so I could make classifiers for cats, dogs... using Imagenet and some Conv nets famous architectures but my problems is if I had an image that contain a human and a cat and a car how can... |
H: Product Recommendation based on purchase history
I am dealing with problem where i have to increase the sales by product recommendation.I only have customer data and product that they have purchased.No ratings,reviews or feedback is present.What approach fit best for my problem.
AI: Even if you don't have ratings o... |
H: Single vs Multiple deep learning networks for multi-label classification?
Given a machine reaches a broken state, there are potentially fixes that can to be applied to get the machine to run again. We'd like to know if, for the problem further defined below, with millions of datapoints, hundreds of features, and te... |
H: Are there free cloud services to train machine learning models?
I want to train a deep model with a large amount of training data, but my desktop does not have that power to train such a deep model with these abundant data.
I'd like to know whether there are any free cloud services that can be used for training ma... |
H: Why is an activation function notated as "g"?
In many cases an activation function is notated as g (e.g. Andrew Ng's Course courses), especially if it doesn't refer to any specific activation function such as sigmoid.
However, where does this convention come from? And for what reason did g start to be used?
AI: The... |
H: How to use k-means outputs (extracted features) as SVM inputs?
l have a dataset of images with their labels.
l put them into a k-means algorithm (as a feature extractor).
Now, l would like to use this new representation of images (features extracted from k-means algorithm) as SVM classifier inputs.
How can l do tha... |
H: SVDD vs once Class SVM
Can some one please explain me what is the difference between one class SVM and SVDD(support vector data description)
AI: Support vector data description (SVDD) finds the smallest hypersphere that contains all samples, except for some outliers. One-class SVM (OC-SVM) separates the inliers fro... |
H: How is a splitting point chosen for continuous variables in decision trees?
I have two questions related to decision trees:
If we have a continuous attribute, how do we choose the splitting value?
Example: Age=(20,29,50,40....)
Imagine that we have a continuous attribute $f$ that have values in $R$. How can I wri... |
H: How to implement a convolutional autoencoder?
I would like to implement a convolutional autoencoder in Tensorflow, but it is not clear how the decoder part should work.
Each layer of the encoding, is a convolutional layer with activation function and then a pooling layer.
But how will the decoding work? I know that... |
H: Working with Data which is not Normal/Gaussian
What happens if my data/feature is not normal? Can I still use machine learning algorithms to utilize such data for predictions?
I noticed in many data sciences courses, there is always a strong assumption of using a normal/Gaussian data. I have always wonder why this ... |
H: How to calculate growth function for a threshold function
I'm working on a homework problem but don't fully understand it. The problem and solution:
I don't understand the definition of the threshold function.
Does it mean to pick one feature and classify the point based on that one feature?
It's the only way I ... |
H: ROC curve shows strange results for imbalanced dataset
I have a classifier with a heavily imbalanced dataset (1000 of each negative label for each positive.)
I'm running a GradientBoostingClassifier with moderate success (AUC .75) but the curve has this strange look:
Any good ideas on what would cause the curve to... |
H: Cosine similarity between query and document confusion
I am going through the Manning book for Information retrieval. Currently I am at the part about cosine similarity. One thing is not clear for me.
Let's say that I have the tf idf vectors for the query and a document. I want to compute the cosine similarity be... |
H: Identifying which known groups are the most similar or most dissimilar
I have a data set of 5 groups and their associations to different interests. The data is structured as follows with 2000+ interests and 5 known groups:
Interest Group1 Group2 Group3 Group4 Group5
01. Sports 10... |
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