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H: Interpreting ROC curves across k-fold cross-validation
I have used a MARS model (multivariate adaptive regression splines) and I have used k fold cross validation for the evaluation of the model, obtaining the following graph:
How would be the interpretation of this model? I understand that in the 6 fold, the mode... |
H: How interpret or what's the meaning of rbm.up results?
I am studying deep learning and the deepnet R package gives me the following example: (rbm.up function Infer hidden units states by visible units)
library(deepnet)
Var1 <- c(rep(1, 50), rep(0, 50))
Var2 <- c(rep(0, 50), rep(1, 50))
x3 <- matrix(c(Var1, Var2), ... |
H: My validation loss is too much higher than the training loss is that overfitting?
I am new to data deep learning. I am educating myself but I don't understand this situation. Where Validation loss is much much higher than the training loss. Can someone please interpret this?
inputs = keras.Input((width, height,... |
H: Orange's Results are not reproducible
I've been watching a few training videos from Orange here and attempted to reproduce the process. They used iris dataset for classification task. When I compared my confusion matrix to theirs, I didn't get the same results.
Is this a problem with Orange software or with sklearn... |
H: What does it mean if the validation accuracy is equal to the testing accuracy?
I am training a CNN model for my specific problem. I have divided the dataset into 70% training set, 20% validation set, and 10% test set. The validation accuracy achieved was 95% and the test accuracy achieved was also 95%. What does th... |
H: Why we need to 'train word2vec' when word2vec itself is said to be 'pretrained'?
I get really confused on why we need to 'train word2vec' when word2vec itself is said to be 'pretrained'? I searched for word2vec pretrained embedding, thinking i can get a mapping table directly mapping my vocab on my dataset to a pre... |
H: For each unique value in a column, count respective unique values in another column
I have a set of tabular data (e.g. csv) representing accesses to a server through a specific protocol . The data follows this format:
server_id | protocol
===================
s1 A
s1 C
s1 C
s1... |
H: Is it feasible to integrate convolutionnal layers as Reinforcement Learning input to learn video game?
Let's say, you want to apply reinforcement learning on a simple 2D game. (ex : super mario)
The easy way is of course to retrieve an abstraction of the environnment, per example using gym and/or an open-source imp... |
H: Confusion about the value of within-cluster SSE
I have a dataset of shape (29088, 11). When I apply the Kmeans where K=2 I get the following plot:
I am surprised that the value of Sum Squared Error (SSE) for C0 (in blue) is smaller than the value of SSE for C1 (in red). Isn't supposed to be the opposite as is demo... |
H: 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 costs to each type of failure? Thank you very much for your help.
AI: A common... |
H: What to do with missing origin city values
Hello fellow data scientists.
I am new in this field, and I face to a problem, for what I need an advice.
So I have data, where one column is product ID, and another which say from which city it originates.
So my question is now what do in the cases, when city value is emp... |
H: Relationship between visualization and feature engineering
Having been in industry for a while, my puzzle on this question still remains unsolved. What exactly is the relationship between visualization and feature engineering? While on Kaggle or elsewhere we can frequently bump into beautiful visualization of data.... |
H: How to Form the Training Examples for Deep Q Network in Reinforcement Learning?
Trying to pick up basics of reinforcement learning by self-study from some blogs and texts. Forgive me if the question is too basic and different bits that I understand are a bit messy, but even after consulting a few references, I cann... |
H: How to deal with missing values that are supposed to be missing?
I am trying to predict loan defaults with a fairly moderate-sized dataset. I will probably be using logistic regression and random forest.
I have around 35 variables and one of them classifies the type of the client: company or authorized individual.
... |
H: Overfitting CNN model - any relation to input image size?
If my CNN model is over-fitting despite trying all possible hyper parameter tuning, does it mean I must decrease/increase my input image size in the Imagadatagenarator?
AI: Overfitting of a model in deep learning is very highly related to number of training ... |
H: Labelling for churn measurement
I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows
a) Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such as purchase date, invoice number, product id,supplier id,project name
b) Inventory ... |
H: Training data for anomaly detection using LSTM Autoencoder
I am building an time-series anomaly detection engine using LSTM autoencoder. I read this article where the author suggests to train the model on clean data only in response to a comment. However, in most cases, it is not possible to find and exlude anomali... |
H: Regularization and loss function
I am currently trying to get a better understanding of regularization as a concept. This leads me to the following question:
Will regularization change when we change the loss function?
Is it correct that this is the sole way that these concepts are related?
AI: I would separate thr... |
H: Activation Functions in Haykins Neural Networks a comprehensive foundation
In Haykins Neural Network a comprehensive foundation, the piecwise-linear funtion is one of the described activation functions.
It is described with:
The corresponding shown plot is
I don't really understand how this is corrected since th... |
H: Plot multiple time series from single dataframe
I have a dataframe with multiple time series and columns with labels. My goal is to plot all time series in a single plot, where the labels should be used in the legend of the plot. The important point is that the x-data of the time series do not match each other, onl... |
H: How do i generate text from ids in Torchtext's sentencepiece_numericalizer?
The torchtext sentencepiece_numericalizer() outputs a generator with indices SentencePiece model corresponding to token in the input sentence. From the generator, I can get the ids.
My question is how do I get the text back after training?
... |
H: VIF Vs Mutual Info
I was searching for the best ways for feature selection in a regression problem & came across a post suggesting mutual info for regression, I tried the same on boston data set. The results were as follows:
# feature selection
f_selector = SelectKBest(score_func=mutual_info_regression, k='all')
#... |
H: What's the purpose of statistical analysis ( statistically important features) vs feature elimination in machine learning
I am developing a classification model for covid19 symptoms (after being ill) and I don't understand statistical analysis importance (some parts of it)
1 Firstly:
Basically we perform statystica... |
H: Standardization in combination with scaling
Would it be ok to standardize all the features that exhibit normal distribution (with StandardScaler) and then re-scale all the features in the range 0-1 (with MinMaxScaler). So far I've only seen people doing one OR the other, but not in combination. Why is that?
Also, i... |
H: Feature selection before or after scaling and splitting
Should feature scaling/standardization/normalization be done before or after feature selection, and before or after data splitting?
I am confused about the order in which the various pre-processing steps should be done
AI: Some feature selection methods will d... |
H: Create new rows based on a value in a column
My dateset is generated like the example
df = {'event':['A','B','C','D'],
'budget':['123','433','1000','1299'],
'duration_days':['6','3','4','2']}
I need to create rows for each event based on the column 'duration_days', if I have duration = 6 the event may ha... |
H: Why does log-transforming the target have a huge impact on MSE value?
I am doing linear regression using the Boston Housing data set, and the effect of applying $\log(y)$ has a huge impact on the MSE. Failing to do it gives MSE=34.94 while if $y$ is transformed, it gives 0.05.
AI: The MSE is sensitive to scale. To ... |
H: Genetic Algorithms (Specifically with Keras)
I can't get my deep genetic algorithm snake game to work and I can't figure out why. At this point, I think it must be either the crossover_rate/mutation_rate or the actual crossover code itself is wrong. I'm hoping someone here can help me with figuring out which.
So, h... |
H: What does a leaf size of 1 in K-neighbors regression mean?
I am doing hyperparameter tuning + cross validation and I'm constantly getting that the optimal size of the leaf should be 1. Should I worry? Is this a sign of overfitting?
AI: leaf_size should have zero effect on the performance of the model. Its effect is... |
H: When to split Test and Training data from the full Dataset
I'm about to put my implementation into a pipeline and I'm now faced with the dilemma on when to actually split the test and training set? I have the following steps that I currently do (the names are self explanatory)
DistinctValuesCleanser
OutlierCleanse... |
H: Sum vs mean of word-embeddings for sentence similarity
So, say I have the following sentences
["The dog says woof", "a king leads the country", "an apple is red"]
I can embed each word using an N dimensional vector, and represent each sentence as either the sum or mean of all the words in the sentence (e.g Word2Vec... |
H: What metrics work well in unbalanced assemblies?
I wanted to know if there are some metrics that work well when working with an unbalanced dataset. I know that accuracy is a very bad metric when evaluating a classifier when the data is unbalanced but, what about for example the Kappa index?
Best regards and thanks.... |
H: forcing decision tree use specific features first
My goal it to force some feature used firstly to split tree. Below, the function splitted tree using feature_3 first. For instance, is there a way to force to use feature_2 first instead of feature_3 ?
from sklearn import datasets
from sklearn.tree import DecisionTr... |
H: DB-Scan with ring like data
I've been using the DBScan implementation of python from sklearn.cluster. The problem is, that I'm working with 360° lidar data which means, that my data is a ring like structure.
To illustrate my problem take a look at this picture. The colours of the points are the groups assigned by D... |
H: Why DQN but no Deep Sarsa?
Why is DQN frequently used while there is hardly any occurrence of Deep Sarsa?
I found this paper https://arxiv.org/pdf/1702.03118.pdf using it, but nothing else which might be relevant.
I assume the cause could be the Ape-X architecture which came up the year after the Deep Sarsa paper a... |
H: Are genetic algorithms considered to be generative models?
My understanding is that these sorts of algorithms can evolve/mutate data to hone in on specific desirable areas in large/difficult to search parameter spaces. Assuming one does this successfully, how does one generate new data/sample from that desirable ra... |
H: Does t-SNE have to result in clear clusters / structures?
I have a data set which, no matter how I tune t-SNE, won't end in clearly separate clusters or even patterns and structures. Ultimately, it results in arbitrary distributed data points all over the plot with some more data points of the one class there and s... |
H: RNN/LSTM timeseries, with fixed attributes per run
I have a multivariate time series of weather date: temperature, humidity and wind strength ($x_{c,t},y_{c,t},z_{c,t}$ respectively). I have this data for a dozen different cities ($c\in {c_1,c_2,...,c_{12}}$).
I also know the values of certain fixed attributes for ... |
H: BERT base uncased required gpu ram
I'm working on an NLP task, using BERT, and I have a little doubt about GPU memory.
I already made a model (using DistilBERT) since I had out-of-memory problems with tensorflow on a RTX3090 (24gb gpu's ram, but ~20.5gb usable) with BERT base model.
To make it working, I limited my... |
H: How do I calculate the accuracy rate of predicting “Fail”? Am I supposed to create a confusion matrix?
Question: ABC Open University has a Teaching and Learning Analytics Unit (TLAU) which aims to provide information for data-driven and evidence-based decision making in both teaching and learning in the university.... |
H: How to set the same number of datapoints in the different ranges in correlation chart
I am beginner in working with machine learning. I would like to ask a question that How could I set the same number of datapoints in the different ranges in correlation chart? Or any techniques for doing that? . Specifically, I wa... |
H: How To Develop Cluster Models Where the Clusters Occur Along Subsets of Dimensions in Multidimensional Data?
I have been exploring clustering algorithms (K-Means, K-Medoids, Ward Agglomerative, Gaussian Mixture Modeling, BIRCH, DBSCAN, OPTICS, Common Nearest-Neighbour Clustering) with multidimensional data. I belie... |
H: Keras Binary Classification - Maximizing Recall
Let me start by saying my machine learning experience is... dangerous at this stage. I'm still a beginner.
I have a binary classification data set of about 100 000 records. 10% of the records are positive and the rest obviously negative. Thus a highly skewed datase... |
H: Interpreting the variance of feature importance outputs with each random forest run using the same parameters
I noticed that I am getting different feature importance results with each random forest run even though they are using the same parameters. Now, I know that a random forest model takes observations randoml... |
H: Coefficients values in filter in Convolutional Neural Networks
I'm starting to learn how convolutional neural networks work, and I have a question regarding the filters. Are these chosen manually or are they generated by the network in training? If it's the latter, are the coefficients in the filters chosen at rand... |
H: Is my model classification overfitting?
Is this possible to be just a bad draw on the 20% or is it overfitting? I'd appreciate some tips on what's going on.
AI: A few comments:
You don't mention number of classes or distribution. Unless the classes are balanced, you should use precision/recall/f1-score instead of ... |
H: Is there a sensible notion of 'character embeddings'?
There are several popular word embeddings available (e.g., Fasttext and GloVe); In short, those embeddings are a tool to encode words along with a sensible notion of semantics attached to those words (i.e. words with similar sematics are nearly parallel).
Questi... |
H: Pretrained vs. finetuned model
I have a doubt regarding terminology. When dealing with huggingface transformer models, I often read about "using pretrained models for classification" vs. "fine-tuning a pretrained model for classification."
I fail to understand what the exact difference between these two is. As I un... |
H: Derivative of MSE Cost Function
The gradient descent:
$\theta_{t+1}=\theta_t-a\frac{\partial}{\partial \theta_j}J(\theta)$
But specifically about $J$ cost function (Mean Squared Error) partial derivative:
Consider that: $h_\theta(x)=\theta_0+\theta_1x$
$\frac{\partial}{\partial\theta_j}J(\theta) = \frac{\partial}{\... |
H: Can anyone tell me how can I get the following output?
Here is my code;
file_name = ['0a57bd3e-e558-4534-8315-4b0bd53df9d8.jpeg', '20d721fc-c443-49b2-aece-fd760f13ff7e.jpeg']
img_id = {}
images = []
for e, i in enumerate(range(len(file_name))):
img_id['file_name'] = file_name[e]
images.append(img_id)
print(... |
H: How does ExtraTrees (Extremely Randomized Trees) learn?
I'm trying to understand the difference between random forests and extremely randomized trees (https://orbi.uliege.be/bitstream/2268/9357/1/geurts-mlj-advance.pdf)
I understand that extratrees uses random splits and no bootstrapping, as covered here: https://s... |
H: Using Sci-Kit Learn Clustering and/or Random-Forest Classification on String Data with Multiple Sub-Classifications
I have a set of data with some numerical features and some string data. The string data is essentially a set of classes that are not inherently related. For example:
Sample_1,0.4,1.2,kitchen;living_ro... |
H: What is the purpose of Sequence Length parameter in RNN (specifically on PyTorch)?
I am trying to understand RNN. I got a good sense of how it works on theory. But then on PyTorch you have two extra dimensions to your input data: batch size (number of batches) and sequence length. The model I am working on is a sim... |
H: How can I use a confusion matrix in image captioning?
I read that a confusion matrix is used with image classification but if I need to draw it with image captioning how to use it or can I draw it in the evaluation model phase for example if yes how can I start?
AI: There's a confusion: a confusion matrix is a stan... |
H: How do I design a random forest split with a "not sure" category?
Let's say I have data with two target labels, A and B.
I want to design a random forest that has three outputs:
A, B and Not sure.
Items in the Not sure category would be a mix of A and B that would be about evenly distributed.
I don't mind writing t... |
H: Can I perform a Logistic regression on this data?
I have the data below:
I want to explain the relationship between 'Milieu' who has two factors, and 'DAM'. As you may notice, the blue population's included in the red population.
Can I apply a logistic regression?
AI: Yes. If you have numeric features for a classi... |
H: Understanding SGD for Binary Cross-Entropy loss
I'm trying to describe mathematically how stochastic gradient descent could be used to minimize the binary cross entropy loss.
The typical description of SGD is that I can find online is: $\theta = \theta - \eta *\nabla_{\theta}J(\theta,x^{(i)},y^{(i)})$ where $\theta... |
H: How to find the number of operation ( multiplication or addition etc) required given a Keras model?
I want to implement an FPGA code or hardware code of a Keras model. As a first step, I want to find the number of mathematical operations required to evaluate a predicted output given a model. The model below is a ... |
H: Building a graph out of a large text corpus
I'm given a large amount of documents upon which I should perform various kinds of analysis. Since the documents are to be used as a foundation of a final product, I thought about building a graph out of this text corpus, with each document corresponding to a node.
One wa... |
H: What is meant by this notation for ensemble classifier error rate
The below is a picture which denotes the error of an ensemble classifier. Can someone help me understand the notation
What does it mean to have (25 and i) in brackets and what is ε^1 is it error of first classifier or the error rate raised to power ... |
H: is it good to have 100% accuracy on validation?
i'm still new in machine learning. currently i'm creating an anomaly detection for flight data. it is a multivariate time series data that include timestamp, latitude, longitude, velocity and altitude of the aircraft. i'm splitting the data into train and test with 80... |
H: How to verify if the behavior of CNN model is correct?
I am exploring using CNNs for multi-class classification. My model details are:
and the training/testing accuracy/loss:
As you can see from the image, the accuracy jumped from 0.08 to 0.39 to 0.77 to 0.96 in few epochs. I have tried changing the details of th... |
H: what degree of fredom one should use while calculating standard diviation for standardizing data
I am writing a function to standardize the data and I found out that we can choose either ddof = 0 or ddof = 1, so I got confused that which one to choose and why? Does this make any difference?
AI: ddof represents the ... |
H: What are the requirements for a word list to be used for Bayesian inference?
Intro
I need an input file of 5 letter English words to train my Bayesian model to infer the stochastic dependency between each position. For instance, is the probability of a letter at the position 5 dependent on the probability of a lett... |
H: Interpreting interaction term coefficient in GLM/regression
I'm a psychology student and trying come up with a research plan involving GLM. I'm thinking about adding an interaction term in the analysis but I'm unsure about the interpretation of it. To make things simple, I'm going to use linear regression as an exa... |
H: Compare string entries of columns in different pandas dataframes
I have two dataframes, df1 and df2, both with different number of rows.
df1 has a column 'NAME', a short string; and df2 has a column 'LOCAL_NAME', a much longer string that may contain the exact contents of df1.NAME.
I want to compare every entry of ... |
H: how to calculate loss function?
i hope you are doing well ,
i want to ask a question regarding loss function in a neural network
i know that the loss function is calculated for each data point in the training set , and then the backpropagation is done depending on if we are using batch gradient descent (backpropaga... |
H: Interpreting cluster variables - raw vs scaled
I already referred these posts here and here. I also posted here but since there is no response, am posting here.
Currently, I am working on customer segmentation using their purchase data.
So, my data has below info for each customer
Based on the above linked posts I... |
H: What is the Purpose of Feature Selection
I have a small medical dataset (200 samples) that contains only 6 cases of the condition I am trying to predict using machine learning.
So far, the dataset is not proving useful for predicting the target variable and is resulting in models with 0% recall and precision, proba... |
H: How to return the number of values that has a specific count
I would like to find how many occurrences of a specific value count a column contains. For example, based on the data frame below, I want to find how many values in the ID column are repeated twice
| ID |
| -------- |
| 000001 |
| 00... |
H: Is it recommended to train a NER model using a dataset that has all tokens annotated?
I'd like to train a model to predict the constant and variable parts in log messages.
For example, considering the log message: Example log 1, the trained model would be able to identify:
1 as the variable
Example, log labeled ... |
H: Can depth be used as a feature when predicting rock type from well log data?
I am trying to predict the lithofacies, i.e. the rock type, from well log data, a project very similar to the one described in this tutorial.
A well log can be seen as a 1D curve tracking how a given property (e.g. gamma radiation, electri... |
H: Classification Produces too Many False Positives or False Negatives
I trying to classify this data set (https://www.kaggle.com/datasets/fedesoriano/stroke-prediction-dataset) to classify if a patient is at risk for having a stroke. As the title says, whatever test I run to classify the patients, I keep running into... |
H: How to fit a model on validation_data?
can you help me understand this better? I need to detect anomalies so I am trying to fit an lstm model using validation_data but the losses does not converge. Do they really need to converge? Does the validation data should resemble train or test data or inbetween?
Also, which... |
H: Combine multiple duplicate categorical variables into a single one for multiple linear regression
I am trying to create a regression model that predicts the box office success of a movie, with one of the explanatory variables being the actors who appear in the film.
My problem is that I decided to do the first 4 bi... |
H: What are the differences between the below feature selection methods?
Do the below codes do the same? If not, what are the differences?
fs = RFE(estimator=RandomForestClassifier(), n_features_to_select=10)
fs.fit(X, y)
print(fs.support_)
fs = SelectFromModel(RandomForestClassifier(), max_features=10)
fs.fit(X, y)
... |
H: Is it good practice for Keras/TensorFlow users to rely on the validation set for testing?
Some sources consider a test/train split, such as with sklearn, to be expected practice, and validation is more or less reserved for k-fold validation.
However, Keras has a somewhat different approach with its validation_split... |
H: Correct way of calculating probability
I have some data which shows how many orders were made by a certain customer group that bought a certain product type:
And the same format but showing how many refunds were made:
I am trying to answer a question:
What is the probability that an order is made by a customer in... |
H: What are the hidden states in the Transformer-XL? Also, how does the recurrence wiring look like?
After exhaustively reading the many blogs and papers on Transformers-XL, I still have some questions before I can say that I understand Transformer-XL (and by extension XLNet). Any help in this regard is hugely appreci... |
H: Do we need the outer discount term when implementing REINFORCE algorithm
I am learning the REINFORCE algorithm, which seems to be a foundation for other algorithms.
I saw the $\gamma^t$ term in Sutton's textbook.
But later when I watch Silver's lecture on this, there's no $\gamma^t$ term.
I read several implement... |
H: Naive Bayes Denominator clarification
I came across an earlier post that was resolved and had a follow up to it but I couldn't comment because my reputation is under 50. Essentially I am interested in calculating the denominator in Naive Bayes.
Now I understand that the features in Naive Bayes are assumed to be in... |
H: Understanding the algebra behind a specific partial derivative equation
I am following this article about neural networks.
Given:
Until here I understand everything, but then he continues to:
I don't understand how he got to that conclusion. I think he skipped some algebra steps that would have made it easier ... |
H: How should I use BERT embeddings for clustering (as opposed to fine-tuning BERT model for a supervised task)
First of all, I want to say that I am asking this question because I am interested in using BERT embeddings as document features to do clustering. I am using Transformers from the Hugging Face library. I was... |
H: How to predict unknown unknowns in machine learning
I am dealing with a problem about classifying bird species through analysing MFCCs. I already built a dataset with 13 MFCCs for two kinds of birds. And I trained the data with Naive Bayes & KNN model. However, when I tried the model with prediction of third bird s... |
H: How to give a 3D Tensor as input to LSTM
I'm having X_train of shape (1400, 64, 35) and y_train of shape (1400,). I want to give X_train as input to LSTM layer and also want to find the Average (using GlobalAveragePooling Layer) of the Output of LSTM at each time step and give it as input to a Dense Layer. For this... |
H: Word representation that gives more weight to terms frequent in corpus?
The tf-idf discounts the words that appear in a lot of documents in the corpus. I am constructing an anomaly detection text classification algorithm that is trained only on valid documents. Later I use One-class SVM to detect outliers. Interest... |
H: implementing forward and backward of a Linear model
I'm implementing the code of this abstraction.
The forward is easy and looks like that:
I don't understand the backward path and how it fit's the abstraction in the first image:
Why is db defined as multiplication of ones of x's shape and dout ?
Why is dw defi... |
H: When combined correlation of features decreases
I'm building a machine learning model in Python to predict soccer player values. I'm trying to predict a "player_value" column containing the value of a specific player. Consider a sample of the columns (features) I'm using.
---------------------------------
appearanc... |
H: How to convert DNA sequences in FASTA format to OneHot Encoded Pandas Dataframe for Neural Networks?
DNA sequences in FASTA format look like:
CATGCATTAGTTATTAATAGTAATCAATTACGGGGTCATTAGTTCA...
I am trying to convert them into one-hot encoded data in a Pandas dataframe so that I can use various neural networks to a... |
H: I do feature engineering on the full dataset, is this wrong?
I am aiming to predict the number of days it takes to sell a given property, let's call this variable "DaysForSale" - in short DfS
Using the DfS I created a variable called "median_dfs_grouped_street_name" which returns the median days it takes to sell a ... |
H: Can we use sentence transformers to embed sentences without labels?
I was trying to use this project :
https://github.com/UKPLab/sentence-transformers
for embedding non english sentences, the language is not a human speaking language, its machine language (x86)
but the problem is i cannot find a simple example wher... |
H: Why does Transfer Learning works better on smaller datasets than on larger ones?
This question is not about the utility of Tranfer Learning compared with regular supervised learning.
1. Context
I'm studying Health-Monitoring techniques, and I practice on the C-MAPSS dataset. The goal is to predict the Remaining Use... |
H: 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 non-numerical variables to numerical variable such that : Math: 0, Scienc... |
H: Removing constant from the regression model
I am trying to calibrate two variables $(X,Y)$ of different measuring techniques from two instruments, the result of the linear regression analysis appears as shown in the image.
The result shows the regression constant is not statistically significant but the model is si... |
H: TF-IDF for Topic Modeling
Can TF-IDF be used a sole method for Topic Modeling ? (I know there are better methods like LDA , LSA etc)
I just want to understand if TF-IDF alone can help us in Topic modeling . If yes , can someone explain how that simple framework works ?
I want to understand the application and capab... |
H: Is it bad to have a lot of one class of Data [K-NN classifier]?
I am trying to train a sklearn K-NN classifier on a labeled text dataset (in Irish). There are 5 classes, 0-4, but there is a lot of variation between how many there are in each class.
What I have done is I've gotten a corpus of Irish text, iterated th... |
H: How Important is Machine Learning to a Data Scientist?
When ever the word data science pops up people generally become quick to move to machine learning. Is that the right thing? For a data scientist isn't the handling of data (collection, pre-processing, visualization, etc.,) more important?
I am aware of the thre... |
H: When should I use normal Q learning over a DQN?
From this article here, it says that using a tabular Q function is less scalable than a deep Q network. I assume that this means that the Q table approach works for some environments, but once they become more complex, they aren't as efficient.
For example, the Frozen... |
H: Types of maps in Interpretable Machine Learning
I have worked on Interpretable Machine Learning (IML) for over 1 year. However, there are some terminologies that always make me confused.
For example, saliency maps/heat maps. Are they same?
Are activation maps visualizations of activation values of a unit(s) in Neur... |
H: Pandas Groupby datetime by multiple hours
I have a log dataset which looks like the following:-
Time event
2020-08-27 07:00:00 1
2020-08-27 08:34:00 1
2020-08-27 16:42:23 1
2020-08-27 23:19:11 1
.
.
.
I am trying to get the count o... |
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