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H: GridSearchCV Decrease performance RF
Can Gridsearchcv params perform worst than default RF?
RF with default values performs rmse_train=4886,r^2_train=0.84, rmse_test=11008,r^2_test=0.22.
RF after GridSearchCV tuning performs worst on train set (rmse_train=9104,r^2_train=0.45, rmse_test=11091,r^2_test=0.21). This is... |
H: Multiple solutions with same minima in MLP with same weights
I came across an excercise on deep learning from here.
It goes as follows:
Consider a simple MLP with a single hidden layer of $d$ dimensions in the hidden layer and a single output. Show that for any local minimum there are at least $d!$ equivalent solut... |
H: Syntax error in function but everything seems correct
I am custom defining a function and following is my function but I get error as below
def saveSlice(img, fname, path):
img = np.uint8(img * 255)
fout = os.path.join(path, f'{fname}.png')
cv2.imwrite(fout, img)
print(f'[+] Slice saved: {fout... |
H: BERT Self-Attention layer
I am trying to use the first individual BertSelfAttention layer for the BERT-base model, but the model I am loading from torch.hub seems to be different then the one used in hugginface transformers.models.bert.modeling_bert:
import torch, transformers
tokenizer = transformers.BertTokenize... |
H: How to create multi-hot encoding from a list column in dataframe?
I have dataframe like this
Label IDs
0 [10, 1]
1 [15]
0 [14]
I want to create a multihot encoding of the feature IDs. It should look like this
Label ID_10 ID_1 ID_15 ID_14
0 1 1 0 0
1 0 0 1 0
0... |
H: GPA prediction of college student
I have a dataset consist of 8 columns and 15600 rows with the following columns:-
1.Entry_academic_year which have 5 discrete value (2558,2559,2560,2561,2562)
2.Faculty (It is the faculty that student has taken like engineering)
3.branch (It is the branch that student has taken ... |
H: 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 achieve this. However I came across another concept, ... |
H: Machine Learning - Euclidian Distance Classifier exercise
I'm taking part in an elective subject at university which mainly focuses on the foundations of Machine Learning.
Now we got our first exercise - this task should be done practically in any language (I've chosen Python). Our teacher doesn't explain the relat... |
H: How to interpret the rec curve for a regression task?
I am using forest fire dataset and applied neural network model. I tried to generate REC curve, this is how it looks like. Pretty weird!!!
I have also applied XGBoost but the REC curve is almost parallel to X-axis.
I don't understand how to make sense out of it... |
H: how to calculate similarity between users based on movie ratings
Hi I am working on a movie recommendation system and I have to find alikeness between the main user and other users. For example, the main user watched 3 specific movies and rated them as 8,5,7. A user who happened to watch the same movies rated them ... |
H: Is probabilistic machine learning just the mathematical background of machine learning?
I wanted to begin with machine learning, I went through the contents of the course on ML by Andrew Ng and found that though the course was based on mathematics, but wasn't too much on the probability or statistics.
But in many u... |
H: Negative log-likelihood not the same as cross-entropy?
The negative log-likelihood
$$
\sum_{i=1}^{m}\log p_{model}(\mathbf{y} | \mathbf{x} ; \boldsymbol{\theta})
$$
can be multiplied by $\frac{1}{m}$ after which the law of large numbers can be used to get
$$
\frac{1}{m} \sum_{i=1}^{m}\log p_{model}(\mathbf{y} | \ma... |
H: Error is occurring setting an array element with a sequence
I have the columns in my Data Frame as shown below:
Venue city Venue Categories
Madison London [1, 1, 1, 1, 0, 0, 0, ...,0,0]
WaterFront Austria [0, 1, 1 0, 0, 0, 0, ....0,1]
Aeronaut Marvill... |
H: ideal algorithms to demonstrate overfitting or underfitting
When one tries to look up concepts such as overfitting and underfitting, the most common thing that pops up is polynomial regression. Why is polynomial regression often used to demonstrate these concepts? Is it just because it can be easily visualised like... |
H: What if irrelevant features impact the outputs?
We know that weather conditions in China is not very useful to predict price of a house in Spain (as life experience). However, when we drop that China's weather condition, the accuracy is reduced largely. Will we keep it?
AI: It would mean that the model trained with... |
H: Low scale ML/statistical techniques for data poor settings
I have two separate problems, but both suffer from a paucity of data problems:
logistic regression
Time series prediction
For logistic regression, I have a tiny dataset with 10 observations which have variables such as:
age, Marital_Status, income, gende... |
H: Keras: apply multiple filters to each feature map in CNN
I am new to Keras, and I want to do the following: take a 2D image, and apply four 2D convolution kernels to it, giving four 2D feature maps. I could accomplish this. But then I want to apply two distinct 2D convolutions to each of those 4 maps, giving 8 fea... |
H: Optimal points of $f(x,y)=x^2 + y^2 + \beta xy + x + 2y$
I am self-learning basic optimization theory and algorithms from "An Introduction to Optimization" by Chong and Zak. I would like someone to verify my solution to this problem, on finding the minimizer/maximizer of a function of two variables, or any tips/hin... |
H: Basic doubt regarding "training" of a YOLO model
So I have just recently started exploring machine learning, and for a project I was required to train the YOLO v5 model. I first tried it on the coco128 dataset:https://www.kaggle.com/ultralytics/coco128..
repository of the yolo v5:
https://github.com/ultralytics/yol... |
H: in binary classification where class labels are {-1, 1} is preprocessing needed?
In machine learning we convert labels using LabelEncoder to convert string ex:{"malignant", "benign"} -> {0, 1}
I am wondering if converting Labels to any other numbers matter, in my scenario to {-1,1}.
If it matters, reason provided w... |
H: reprocessing steps for images before training classification models
I have a data set of images for classification task.
I read some articles about image reprocessing (before training CNN models) which summarize in those steps:
scale image values (img / 255.0)
remove noise (using Gaussian blur)
morphology
I'm ... |
H: How does the random forest vote work?
I have a question. How is the voting done in random forests. I can't understand rationally, since we have a bootstrap sample drawn, and have built dection trees based on them, where is the new data point taken from to do the voting and extract the results?
AI: Always separate t... |
H: Criteria for saving best model during training neural network?
I am doing 4-class semantic segmentation with U-net using generalised dice loss as loss function.
General approach to save best model during training is to monitor validation loss at each epoch and save the model if val loss decreases than previous mini... |
H: Slight confusion on the learning process
Hi guys I have a slight confusion on the learning process of neural networks.
When the input layer receives inputs, goes through the hidden layers and then into the output layer. How does the neural network know that the outputs at the output layer are incorrect?
When the er... |
H: Linear Learning Machines
I was reading about Linear Learning Machines (LLMs) and learned that it is closely related with SVMs. Would like to know an example of any concrete problems that can be classified by LLM as I couldn't find any promising example or explanation for this.
Appreciate your time.
AI: Not sure at ... |
H: What's the issue with my code for visualizing linear regression in 3 dimensions with matplotlib?
I am trying to use linear regression that takes two variables "Idade" and "LF" and tries to predict a third one, "DGAF". I'm trying to both do the scatterplot with the observations and the model prediction on the same g... |
H: Can someone explain to me how to use a predictive model to predict something other than the training set
So let's say I create a logistic model to predict who will open a loan based on a based email list that includes who opened and who didn't that's 90% accurate. The model says age, income, bank engagement are thr... |
H: What exactly is convergence rate referring to in machine learning?
My understanding of the term "Convergence Rate" is as follows:
Rate at which maximum/Minimum of a function is reached, so in logistic
regression rate at which gradient decent reaches global minimum.
So by convergence rate I am guessing it is measu... |
H: Best parameters to try while hyperparameter tuning in Decision Trees
I want to post prune my decision tree as it is overfitting, I can do this using cost complexity pruning by adjusting ccp_alphas parameters however this does not seem very intuitive to me.
From my understanding there are some hyperparameters such a... |
H: Using vgg16 or inception with wights equals to None
When using pre-trained models like vgg16 or inception,
it seems that one of the benfits of using pre-trained model, is to save up time of training.
Is there a reason to use the pre-trained models without loading the weights ? (use random weights) ?
AI: The advanta... |
H: Grouping with non-sequential index (datetime) [Pandas] [Python]
I am working in Python, I have a DataFrame whose index is of type DateTime, the times of the index are not continuous. You can see that the first three data are in sequence and after the third data it goes directly to minute 50. The entire DataFrame ha... |
H: Checking trained CNN on the images
I trained my CNN (model) classifier and want to check it on some new images. I have image x, so this syntax works for me for one image:
torch.argmax(model(x))
What if I want to classify 2 more images (different classes), let's say images y and z? Should I for every image write a... |
H: Do Activation Functions map to Higher Dimensions?:
I just started learning tensorflow and I have a question regarding activation functions used in neural networks, I watched a 3b1b video a while ago and it seems it squished the value into an interval like sigmoid does so by squishing it between 0 and 1 so we could ... |
H: Flag consecutive dates by group
Below is an example of my data (Room and Date). I would like to generate variables Goal1 , Goal2 and Goal3. Every time there is a gap in the Date variable means that the room was closed. My goal is to identify consecutive dates by room.
Room Date Goal1 Goal2 Go... |
H: How to implement random cropping during training?
I'm developing a U-net like model which segments the damaged tissue of the brain between two time-points in Multiple Sclerosis patients. The model is given the baseline and follow-up images as x and the segmentation mask as y. The images are 3D (192, 218, 192) and t... |
H: KNN Variance using a high value of K and cross-validation
it has come to my understanding, that a value of K=1, gives a high variance because we are only using only one data point, hence we are very likely to model the noise in that training example.
Bias: It will take the value of point 3 as it’s the closest one.... |
H: The affect of bootstrap on Isolation Forest
I've been using isolation forest for anomaly detection, and reviewing its parameters at scikit-learn (link). Looking at "bootstrap", I'm not quite clear what using bootstrap would cause. For supervised learning, this should reduce overfitting, but I'm not clear what the e... |
H: What happens when the vocab size of an embedded layer is larger than the text corpus used in training?
Full disclosure this question is based on following this tutorial: https://tinyurl.com/vmyj8rf8
I am trying to fully understand embedded layers in Keras. Imagine having a network to try and understand basic sentim... |
H: Handling categorical data with more over 100 unique classes
I am working with a pure categorical data set. And some classes have more than 100 unique values.
I could not find any appropriate encoding possibility. So I created a SQL table, where each value got its ID. Then I extracted the IDs and used it in ML Class... |
H: Transformer: where is the output of the last FF sub-layer of the encoder used?
In the "Attention Is All You Need" paper, the decoder consists of two attention sub-layers in each layer followed by a FF sub-layer.
The first is a masked self attention which gets as an input the output of the decoder in the previous st... |
H: pandas groupby.count doesn't count zero occurrences
I am using groupby.count for 2 columns to get value occurrences under a class constraint. However, if value $x$ in feature never occurs with class $y$, then this pandas method returns only non-zero frequencies. Is there any solution or alternate method?
The script... |
H: Pretrained models for Propositional logic
Are there any pretrained models which understand propositional logic?
For example, the t5 model can do question-answering. Given a context such as "Alice is Bob's mother. Bob is Charlie's father", t5 can answer the question "Who is Charlie's father" correctly, but it cannot... |
H: How to know the state-of-the-art recommended approaches for data science?
Data science, AI, NLP, and visualization are changing so fast. I wonder if there is a way/blog that shares the latest updates and recommended approach using certain techniques or avoid using others. For example, many NLP books are old and the... |
H: Model that predicts probability of correctness of another model
Problem:
Given a neural network for image classification with $1000$ classes, the objective is to create another model which will output the probability of the neural network giving the correct prediction for a specific input image.
Thoughts:
My ideas ... |
H: Why does this paper claim to have found a minimal width of $d_{in}+1$?
Why does this paper (click the link) claim to have found a minimal width of $d_{in}+1$ in the abstract? I mean, if you read the main result, it seems like they only find a universal approximator with width $d_{in} + d_{out}$. What am I missing o... |
H: Data Leakage when preprocessing categorical features?
I am fairly new to machine learning. I came across the concept of Data Leakage. The article says that always split the data before performing preprocessing steps.
My question is, do steps such as discretization, grouping categories to a single category to reduce... |
H: How does epochs related with converging the model?
I have read on Internet that epochs is used to give the time for the model to converge but I don't know how ? . I was thinking that epochs is used because to train the model sufficient times . How does model convergence relates with epochs . Also tell me that why e... |
H: Feature importance with Text features
I would like to determine features importance in several models:
support vector machine
logistic regression
Naive Bayes
random forest
I read that I will need an agnostic model, so I have thought to use performance_importance (in python).
My features look like
Text (e.g., The... |
H: Normalization vs standardization for image classification problem
For day and night image classification, is it better to normalize or standardize images? In general, when should I use each method? I am interested in with example why one method is preferred over another one?
Here, by normalization, I mean dividing ... |
H: How the Support Vector Machine will perform if the bias b = 0 in the equation of hyperplane?
We have a soft margin linear SVM and the equation is as follows :
How the SVM will perform if b = 0, means the hyperplane is passing through the origin ?
AI: I think that it will simply behave as a normal SVM, with the dif... |
H: How does a random forest algorithm deal with a few irrelevant input variables
I have a list of variables from which I would like to train a Random Forest Algorithm. I suspect that a few of my input variables, which have noisy distributions, won't be able to predict much. Can I use them anyway, knowing the algorithm... |
H: How do you choose an appropriate $k$ to achieve $k$-anonymity for data?
How do you choose an appropriate $k$ to achieve $k$-anonymity for a data? What methods exist that are agnostic to the business context for the problem?
AI: In most cases $k$ emerges from the volume and nature of data, plus trhe anonymity method... |
H: Do generative model produce varying outputs for same input
I am new to data sciences. I believe the generative model generate responses on-the-fly for a valid user input. Is it correct to assume that such models would generate different responses for the same question?
For e.g: if we trained the model on say medica... |
H: How to mantain the nested structure of a tf.dataset after applying map?
I'm creating a tf.dataset object containing 2 images as inputs and a mask as target. All of them are 3D in grayscale. After applying a custom map, the shape of the object changes from ((TensorSpec(shape=(), dtype=tf.string, name=None), TensorS... |
H: SGDClassifier - Why do I need to use argmax instead of argmin to find the lowest threshold satisfying given precision?
I am an experienced programmer, but new to Python and data science. I am following Aurelien Gerone's book and I don't understand one thing.
I create SGDClassifier and calculate its precision_recall... |
H: Difference between PCA and regularisation
Currently, I am confusing about PCA and regularisation.
I wonder what is the difference between PCA and regularisation: particularly lasso (L1) regression?
Seems both of them can do the feature selection. I have to admit, I am not quiet familiar with the difference between ... |
H: LSTM classification with different sizes
I'm relatively new to the world of recurrent neural nets and I'm trying to build a classifier using an LSTM model to predict HIV activity from a given molecule (the original dataset can be found here ).
I have sequences of different lengths (from few dozen to almost 400 char... |
H: Machine learning problem with only original data without test and validation data
I am new to machine learning and I am trying to solve a problem where I have to predict if a customer will buy a home insurance product or not.
I have got a dataset which tells me that which of the bank's customer bought a mortgage f... |
H: How useful is Bayesian Inference
Last few months, I had been exposed to Bayesian Inference in ML course
With further investigation, I come to place where there is MCMC technique to simulate the posterior distribution.
It seems interesting. However, I am not sure if it is really useful in the industry?
Does anyone h... |
H: Is there such thing as linear and non-linear data?
While doing machine learning projects we've heard that logistic regression works well with "Linear data" and decision tree works well with "non-linear data"
However concept of linear and non-linear data does not make sense. To me only linearly separable data and no... |
H: Training set Distribution and Activation function/Loss function correlation
How should the probability distribution of the training set influence the choice of the activation function / loss function?
For instance if I have a Multinoulli distribution, which activation function should I choose? And why?
I can't ge... |
H: CNN Design for Counting on Simple Images
This is the first CNN I'm designing following college examples and assignments. I'm working on a CNN that I'd like to use to classify images by the number of shapes on them. My basic problem is that I can't seem, to get the CNN to respond (accuracy and val_accuracy are flat)... |
H: Is it better to use F1 score or AUC metric for imbalanced data classification?
I have a text classification problem, where the "positive" examples are the minority. What metric is better to use for binary classification for this case - F1-score or AUC?
AI: F1-score and AUC are two evaluation measures for binary cla... |
H: Hidden Markov Model
I am trying to find answers to the following questions. Can someone please help. This is a Hidden Markov Model with 7 states and 4 observations. I have worked out the following solution but still need help with parts ii & iii.
Solution:
I.
GATTAG
= 1* 1 * 0.5 * 0.25 * 0.2 * 0.5 * 0.4 * 0.15 * 0... |
H: What exactly is the linear layer in the transformer model?
Please see this image:
There are linear layers to modify the Query, key and value matrices and one linear layer after the multi head attention as they mention also from here:
Are these linear layers simply dense or fully connected layers? Let's consider t... |
H: Understanding LSTM text input
I am an beginner in text generation and and deep-learing but I like to get in touch with it. Currently I am learing about LSTM networks and VAEs for text generation. I would like to read a sequence at once and output another sequence. What I learned from this post is that the input sha... |
H: IS there any way we can add range in hyperparameter tuning of Decision Tree?
For example,
"min_samples_leaf":[1,2,3,4,5,6,7,8,9,10],
'criterion':['gini','entropy'],
"max_features":["auto","log2","sqrt",None],
"max_leaf_nodes":[None,10,20,30,40,50,60,70,80,90] }
but i wa... |
H: Image classification convolutional neural networks
I am trying to solve this problem by using a convolutional NN to classify an image data set to check the type of disease it is. I have reached task 1b and trying to implement the training loop. However, I am getting an error and can't understand how to implement th... |
H: is SST=SSE+SSR only in the context of linear regression?
the problem of regression is to minimize the sum of squared errors, i.e. $\sum\limits_{i=1}^n (y_i - \hat{y}_i)^2 = 0$ .
But only in linear regression could you use the expression $\hat{y}_i = \beta_0 + \beta_1.x_i$ , then minimize the sum of squared errors w... |
H: How to train and evaluate machine learning models with growing/changing datasets over time
Assume that you have a classification machine learning model, and you start with an initial dataset that contains 3 classes. You split the initial dataset into training/testing spits, you train the initial model and evaluate ... |
H: Pytorch: Starting with a high loss value, but the loss converged at the end. I dont know if the model could start with a loss > 100. Help!
I have been trying to attempt plant disease detection using transfer learning methods. I chose ResNet50 first. I also performed a baseline model which is a CNN model. In resnet5... |
H: How to classify a set of words into one of the given labels
I have three labels: amusement, calm and energetic.
I get sets of words like:
Set1 = {Cloud
Sky
People in nature
Plant
Flash photography
Happy
Shorts
Grass
Leisure
Recreation}
Set2 = {Plant
Green
Natural landscape
Natural environment
Branch
Tree
People in ... |
H: Can a machine learning model be used as some kind of compression?
I'm trying to understand how machine learning is working. I read a lot and now came into my mind that it could be missuses in a practical way. I also hope that this question is on topic here.
Please correct me if I have some wrong assumptions:
All m... |
H: regression with noisy target vairable
How can I approach a regression problem where the input data is not noisy but the target variable is noisy? Are there any regression algorithms that are robust to a noisy target variable?
Also, is it possible to de-noise the target variable somehow? If so, how?
AI: It depends h... |
H: Creating radial basis for linear regression Python
I'm trying to do time series forecasting with linear regression like it's done in this video: Radial basis forecasting starting from 5:50.
I understand the basic idea of basis, but I don't think I understood the usage of it in time series data correctly. I have a P... |
H: Computing a cumulative distribution function in Python
I'm trying to compute the distribution function of any of the usual distributions in Python... However, all the methods I've seen involve first drawing N samples from said distribution, and then order them somehow, and then do a cumulative sum.
In Mathematica, ... |
H: TPOT machine learning
I trained a regression TPOT algorithm on Google Colab, where the output of the TPOT process is some boiler plate Python code as shown below.
import numpy as np
import pandas as pd
from sklearn.ensemble import ExtraTreesRegressor
from sklearn.model_selection import train_test_split
from sklearn... |
H: Applying the same changes to the test set
I'm busy working through Aurélien Géron's book. (Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow)
The idea is to split the data into train and test set as early as possible in order to avoid data snooping bias. Afterwards changes are made to the data.
My ... |
H: Handling nominal category features in decision tree
I have been reading some stackoverflow questions on how to handle nominal features for decision tree (sklearn implementation).
One of the answer states that :
Using a OneHotEncoder is the only current valid way, allowing arbitrary splits not dependent on the label... |
H: Extremely negative r^2
I use a linear regression to predict house prices (https://www.kaggle.com/c/house-prices-advanced-regression-techniques/overview). My linear regression sometimes works great with R^2 of 0.8 and sometimes really sucks with R^2 of - 20000000000000 (Yes, really that bad). My data is scaled (with... |
H: In U-Net, is there a non-linearity (relu) in up-convolution layer?
I am doing semantic segmentatio using U-Net. I was wondering whether to include 'relu' activation or not in the up-convolution layer?
x = Conv2DTranspose(filters, kernel_size) (x)
OR
x = Conv2DTranspose(filters, kernel_size, activation='relu') (x)... |
H: What is the impact of changing image sources on an image recognition?
I have a fairly general question pertaining to an image recognition ML model. I’ve recently developed an image recognition model using a single camera collecting more than 5000 images and then trained/developed the model.
My question is if I chan... |
H: dividing Mean by standard Deviation meaning
I have played around with logistic regression a little using movement data intervals that are prelabeled as either resting or active.
I now found that if I divide the mean movement of the individual intervals by the intervals standard deviation, the outcome is quite a goo... |
H: In clustering, sequence number such as customer ID and dates such as purchase date should be dropped?
I am learning K-means clustering and found that in most datasets, there are sequence number such as customer ID and dates such as purchase date.
I don't see any use in them for clustering.
Should I include them for... |
H: What the differences between self-supervised/semi-supervised in NLP?
GPT-1 mentions both Semi-supervised learning and Unsupervised pre-training but it seems like the same to me. Moreoever, "Semi-supervised Sequence Learning" of Dai and Le also more like self-supervised learning. So what the key differences between ... |
H: What if outliers still exist after variable transformation?
I have a variable with a skewed distribution.
I applied BoxCox transformation and now the variable follows a Gaussian distribution. But, as seen in the image below in the boxplot, outliers still exist.
My question is:
Although after transformation, the v... |
H: Model accuracy when training on GPU and then inferencing on CPU
When we are concerned about speed, GPU is way better than CPU.
But if I train a model on a GPU and then deploy the same trained model (no quantization techniques used) on a CPU, will this affect the accuracy of my model? Can the accuracy of the same mo... |
H: Dummy vectors and performance measurement for vector search Face Recognition
I have about thousands of person face (from celebrity dataset LFW), which each person represented by 512 x 1 vector. I stored it on vector DB to build face searching system using embedded feature (MTCNN for face detection and arcface for e... |
H: AUC higher than accuracy in multi-class problem
I stumbled upon a 3-class classification problem where all compared classifiers yield a higher AUC than accuracy (usually around 10% higher). This happens both when the dataset is balanced or slightly imbalanced.
Now, after looking at this answer: Why is AUC higher fo... |
H: Replace a value in pytorch tensor
t=tensor([0.1 0.2 0.3 0.4 0.5 0.6])
now i need to modify this existing tensor t as follows:
t=tensor([0.1 0.2 0.7 0.4 0.8 0.6])
I tried as follows:
t=tensor([0.1 0.2 0.3 0.4 0.5 0.6])
a=tensor([0.1 0.2 0.7 0.4 0.8 0.6])
index=range(len(a))
t.index_copy_(0,index,a)
But still it i... |
H: pytorch dataloader tensor modification
T=tensor([101,123,414,463][234,903,313,341]...)
train=TensorDataset(T)
train_dataloader=Dataloader(train)
Now I would like to update tensor T[0] i.e tensor
T[0]=tensor([101,123,567,463])
for this i have tried as follows:
train_dataloader.Dataset[0].index_copy_(0,tensor([2]),... |
H: Suitable instance counting CNN for training on polygonal masks
I have a medical dataset labeled with polygonal masks (rather than rectangle boxes). It works well for pixel annotation with UNet to generate masks of healthy vs damaged skin. Now I need to do instance counting. Most of the CNNs like YOLOv4 consumes bou... |
H: ZeroR as performance baseline for binary classfication model?
It is known that ZeroR model is used predict the majority class in a given data set.
Having said that, is ZeroR a suitable performance baseline provided one has a balanced data set (50/50)?
If not, what would be a good baseline for a Naive Bayes classifi... |
H: What does my learning curve indicate?
I have performed logistic regression. And I am getting an accuracy of 77% with my current model. I divided my training set into cross validation set and train set. And I plotted a learning curve (graph of training examples vs cost function for train set and cost function of cro... |
H: Should I do one hot encoding before feature selection and how should I perform feature selection on a dataset with both categorical and numerical data
a newbie here. I am currently self-learning data science. I am working on a dataset that has both categorical and numerical (continuous and discrete) features (26 co... |
H: Feeling Stuck on a Beginner – Intermediate level
Over the past two years, I have been working as a full-time data scientist for a government company. As the sole data science team in the organization, our job is a hybrid between data science and machine learning engineering. We need to research and develop ml solut... |
H: Which model is best for object detection which is trained on COCO dataset?
I want to do Object Detection and Segmentation. I want to find out which models are trained on COCO-Dataset eg YOLO etc. But I want to find out which model has the highest accuracy and lowest time. In short which model is best for object det... |
H: Data cleaning in Pandas, where the csv file has all data of each row in 1 field
I have really messy data that looks like this:
As you can see all the data in each row is contained in 1 column separated by a semi colon.
How do I arrange this data so that they are spread out over more columns? For example, category_... |
H: Why the gradient of a ReLU for X>0 is 1?
Gradient is derivative of several variables.
I can't understand why is the gradient of a ReLU for X>0 is 1 ? and 0 for x < 0 ?
I tried to search for proof and examples but didn't found any good examples.
AI: The ReLU function is defined as follows: $f(x) = max(0, x)$, mean... |
H: How to encode a sentence using an attention mechanism?
Recently, I read about one of the state-of-the-art method called Attention models. This method use a Encoder-Decoder model. It can find a better encoding for each word in a sentence. But how can I encode a full sentence?
For example, I have a sentence "I love r... |
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