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I want a proficient developer to create a recommendation system geared towards library users. It should employ a variety of machine learning techniques including KNN, MF, Association Rule Mining, Decision Tree, Naive Bayes, MLP, and Ensemble Learning. The system’s effectiveness should be evaluated using several methods as below: - RMSE - MAE - MSE - Accuracy - Precision Recall - F1 score Use Book Crossing Dataset Code must be in python and don't use specific recommender system library i.e., surprise etc. The successful freelancer must have appreciable knowledge and expertise across these various machine learning techniques, and previous experience building effective recommendation systems. Experience working on recommendation systems for a library or similar institutio...

... 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 388-2, 388-3, 388-4, etc. These are different variations of test sheets of the dataset numbered 388 in ...

... 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 388-2, 388-3, 388-4, etc. These are different variations of test sheets of the dataset numbered 388 in ...

... 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 388-2, 388-3, 388-4, etc. These are different variations of test sheets of the dataset numbered 388 in ...

...The last time we filled this job position for over 2 years. 1) Data Analytics with Python Course: Content (introduction to python, data wrangling with pandas, descriptive statistics with python, data visualization with seaborn, t-test/anova /chi-square tests with python, correlation, regression with statsmodel) 2) Machine Learning with Python Course: Content classification(dcision trees, knn, naive bayes, logReg, classifier evaluation) regression (linear regression with normal equation, stochastic gradient descent, polynomial regression, ridge regression, lasso regression, elastic net, early stopping, regression trees) advanced supervised learning concepts (feature extraction, imbalanced data ,cross-validation, hyperparameter tuning with grid and random search, overfitting/und...

... 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 388-2, 388-3, 388-4, etc. These are different variations of test sheets of the dataset numbered 388 in ...

Do zrealizowania dwa projekty z moimi własnymi bazami danych w KNIME: 1. KNIME REGRESJA LINIOWA Zbuduj model regresji liniowej dla danych AmesHousing. Wypróbuj różne kombinacje predyktorów (zmienych niezależnych) i znajdź taką, która daje najlepsze R2 adjusted. Przeprowadź kilka prób dla różnych podziałów danych na zbiór treningo...podziałów danych na zbiór treningowy i testowy i zapisuj wyniki w pliku excela (wyjściem węzła Numeric Scorer ma być Excel writer). Sprawdź jak wynik się zmieni jeśli zastosujemy węzeł regresji wielomianowej. KLASYFIKACJA Zbuduj Knime workflow, który zastosuje do danych ClevelandHeartData następujące klasyfikatory: Logistic regression Decision tree Random forest Tree ensemble le...

Urgently seeking a highly skilled WordPress developer available on February 2, 2024, and potentially over the weekend. The project involves complex WordPress tasks, including speed optimization, addressing Linux issues, and resolving core WordPress challenges. Key Require...preferably the following weekend. Advanced WordPress Skills: The candidate should have expert skills in WordPress to tackle complex technical issues. Proven track record in significantly improving WordPress site performance. Work must be done on VM/Remote machines. We do not grant admin access for local work. This is a firm policy. Requests for admin access will be viewed as unprofessional and naive. We believe in professional trust but not in handing over sensitive access to new acquaintances from a freelance...

Mengklasifikasikan data menggunakan python dengan algoritma naive bayes. contoh flow: Frontend mengirim data -> (Klasifikasi) data di python -> passing balik ke frontend. (hanya mengerjakan di klasifikasi) contoh data yang dikirim dari frontend: [51, 68, 25, 8, 29, 22] hasil yang diharapkan: Baik/Sedang/Tidak Sehat/Sangat Tidak Sehat/Berbahaya perhitungan data berdasarkan dari data csv dibawah, terimakasih.

I'm looking for a talented Python programmer who can create a stack ensemble using multiple machine learning algorithms. The successful freelancer will: - Develop a stack ensemble using: - Random Forest (RF) - Support Vector Machine (SVM) - Logistic Regression (LR) - K Nearest Neighbor (KNN) - Naive Bayes - Compare the output through voting with a trained Artificial Neural Network (ANN). I am seeking a freelancer who has a deep understanding of these algorithms, can showcase their ability to deploy them effectively and explain their approach in a detailed project proposal. The proposed solution should provide comprehensive code implementation and commentary explaining the methods used and their effectiveness. Dataset Utilization: - The KDD-NSL dataset - The UNSW-N...

...basic tweaks. It’s an e-commerce site rich in content, demanding optimizations that maintain high performance and smooth user experience. Requirements: Proven track record in significantly improving WordPress site performance. Work must be done on VM/Remote machines. We do not grant admin access for local work. This is a firm policy. Requests for admin access will be viewed as unprofessional and naive. We believe in professional trust but not in handing over sensitive access to new acquaintances from a freelancer website. The focus is not only on achieving high PageSpeed scores but also on ensuring the site remains robust, user-friendly, and visually intact. Project Pricing and Completion: This project is on a fixed-price basis. Your proposal should include your rate for ...

The aim of this project is to implement a mul4nomial Naive Bayes model for a sen4ment analysis task using the Ro=en Tomatoes movie review dataset. This dataset is derived from the "Sen4ment Analysis on Movie Reviews" Kaggle compe44on1, that uses data from the works of Pang and Lee [1] and Socher at al. [2]. Obstacles like sentence nega4on, sarcasm, terseness, language ambiguity, and many others make this task very challenging

I am looking for a freelancer to build a classification model using Rstudio codes to identify spam vs. non-spam emails. The dataset provided is small, with less than 1000 emails. Requirements: - Proficiency in Rstudio and machine learning algorithms - Experience with building classification models - Knowledge of Naive Bayes algorithm The ideal freelancer should have expertise in Naive Bayes algorithm and be able to implement it using Rstudio codes. Additionally, the freelancer should have a good understanding of email data and spam detection techniques. I attached the code I currently have and the dataset for reference.

The aim of this project is to implement a multinomial Naive Bayes model for a sentiment analysis using Rotten Tomatoes movie review dataset.

Writing Python code (by colab) 9 Models: 1-Decision Tree Classifiers 2-K-Nearest Neighbors 3-Gaussian Naive Bayes 4-ANN 5-SVC 6-LogisticRegression 7-RandomForest Classifier 8-AdaBoostClassifier 9-XGBoost) the link to the dataset will be sent later.

...fine-tuning a project on chatgpt for university exam questions topic detection. The specific purpose of utilizing chatgpt for this task is to enhance the student learning experience. The most important part for me to understand would be learning how to improve the model day by day and detecting the best way to find the topics of the questions. It does not have to be done through chatgpt. SVM or Naive Bayes might be other ways if they can also give good results. -Finding some example questions and their topics determined by education system -Converting the PDFs to texts and making it ready for the model -Teaching the model about these topics and some parameters about the question like the -Giving the model new questions and asking the questions' topic -Learning the mista...

...complexity of the algorithm, and my maximum accepted complexity is O(n log n). The task is to implement a Suffix array algorithm for exact string matching. I'm given a header file with declared functions that have to be implemented in a separate .cpp file. construct function - see , which gets a suffix array to fill and the text, constructs the suffix array and returns it. Use the naive construction method with std::sort. Note that a suffix array never stores strings, only their starting positions in the original text. The running time of the construction method should therefore be O(n*logn*c), where c is the cost for comparisons(!) of strings. Unlike the theoretical tasks, it's not required an extra $ at the end of the text. We define that a prefix of a string X is l...

...the module that while there are still more documents to be processed, accepts a document as a list of tokens (omit punctuation) and outputs term-docID pairs. Instead of appending new term-docID pairings to a list, make sure you directly append the docID to the postings list for the term. You may use a hash table. No boxes required. (a) compare timing of this SPIMI inspired procedure with the naive indexer (for 10000 term-docID pairings). (b) compile an inverted index for Reuters21578 without using any compression techniques docID hint: Use the NEWID values from the Reuters corpus to make your retrieval comparable. Subproject II: Convert your indexer into a probabilistic search engine 1. using the assumptions made about independence of terms and documents etc. and 2. using ...

...the module that while there are still more documents to be processed, accepts a document as a list of tokens (omit punctuation) and outputs term-docID pairs. Instead of appending new term-docID pairings to a list, make sure you directly append the docID to the postings list for the term. You may use a hash table. No boxes required. (a) compare timing of this SPIMI inspired procedure with the naive indexer (for 10000 term-docID pairings). (b) compile an inverted index for Reuters21578 without using any compression techniques docID hint: Use the NEWID values from the Reuters corpus to make your retrieval comparable. Subproject II: Convert your indexer into a probabilistic search engine 1. using the assumptions made about independence of terms and documents etc. and 2. using ...

I am looking for someone to create a prediction system to help me predict drug activity. Specifically, I want to use decision tree and naive bayes to understand the efficacy, toxicity and interactions of drugs. Furthermore, I will provide a dataset for the prediction models in order to get the best results. Therefore, I am looking for someone knowledgeable in data analysis and prediction models who can help me generate accurate predictions.

In this Application you will implement two different naive Bayes approaches. In class we have considered document representations based on a bag-of-words. In this Application our “documents” 1 2 scikit-learn () is a popular tool for doing many machine learning tasks in Python. It includes implementations of many classifiers (including naive Bayes, but we’re implementing it ourselves in this Application ). 1 ...................................................... requirements details in attached section You will submit: 1)Complete source code zip file 2)Output running video of this application 3)Report 4)write details code comments Remember: you can't do anything outside this requirements

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I leave here a zip with all the screens that need to be done, please send your proposal and deadline soon, profiles outside the scope will be discarded and stupid questions will also be discarded

Hi , I’m looking to create food delivery app, I don’t mind it being web app or naive , please if you can handle the project contact me

Hi , I’m looking to create food delivery app, I don’t mind it being web app or naive , please if you can handle the project contact me

...comprehensive Beginner's level written tutorial on the machine learning classifier, Naive Bayes, using the Python language. This tutorial should be exceptionally understandable and easy to follow. It should include step by step instructions with appropriate explanations, illustrations, and example code. It should be insightful enough to give readers a good understanding of the topic and help improve their problem-solving skills. The tutorial should help anyone new to programming comfortably follow the instructions without needing prior programming knowledge. It needs to include code explanations that readers can easily understand. I will also need example codes so readers can test their understanding of the basics of Naive Bayes. It needs to be concise and detailed en...

Logo design for an online language learning platform - Looking for a professional logo design - The logo should be plain without any images. - The letters 'N' in both the words should be highlighted. - The logo should be creative and should focus on the similar letters between the words 'naive' and 'native'. - Should contain text in white colour only - Need the project completed ASAP Ideal Skills and Experience: - Strong graphic design skills - Experience in creating professional and modern logos - Ability to work quickly and efficiently to meet tight deadlines

I am looking for a skilled designer to creates some company's branding materials. The specific branding materials needed for this project include logo design, Business Profile Brochure, and Business Cards. I am open to suggestions and do not have any specific design elements in mind however, must use Dark green and Naive blue colour. However, I want the branding material to convey a feeling of professionalism and trustworthiness for my company. Ideal Skills and Experience: - Strong portfolio showcasing previous logo designs - Ability to create visually appealing and unique designs - Understanding of branding and its impact on a company's image - Excellent communication skills to understand and incorporate client's vision - Attention to detail and ability to meet d...

...project further with you. Description of the project: We have a LSTM RNN prediction model that predicts future CPU usage (next value). However comparing the performance of this model with naive forecast, we find that MSE of our model is higher than MSE of naive forecast. That means our model doesn’t perform well. For this reason, we need someone who knows about prediction models, RNN, and LSTM. The requirements are the following: Tune the RNN model to get better prediction than naive forecast. Get train and test MSE Get train and test RMSE Test MSE of RNN model must be better (lower) than MSE of naive forecast model Complete and clear documentation about how the tuning process was made Deliver document guides about how the test was made. Delive...

I am looking for an experienced Excel expert to create a custom Quantitative Analysis file containing formulas and functions that will be used for data analysis. The so...solutions should be robust and support a variety of data types. The Excel file should not be restricted to any particular version, so that it can be adapted to any version of Excel. It should be able to support basic as well as advanced formula functions ( MAD & Naive Formula ). The key aim is to develop an efficient and accurate process of data analysis. The final output should be an Excel sheet that can be used easily for data analysis. Important Notes ==============: Please fill the missing data accordingly with using (MAD & Naive Formula) The delivery should be today The Excel sheet attach...

Tasks: 1. Fit data in to Gaussian Naive Bayes. Use all the data for fit 2. Use to test the fitted model. 3. Output two files - one for the fitted model and one for the test data. 4. Format of the output is in and 5. Do all the work using Python and sklearn library 6. Write simple code Once I am satisfied with this task, I will post a separate job for you to do the samething with Decision Trees Multinomial NB KNN Logistic Random Forest

The attached Excel file contains 394 rows of data. The data have 7 input features (A-G), and one output result (H). I want to use these data to build a model such that for any new set of data, I can predict the probability of Yes or No. I want to try using Naive Bayes first. The coding should be done in Python. Please keep the code simple. Also suggest other algorithms that may produce better results for this problem (Decision Tress?). Please state how long it will take before you can give me the results.

I have a dataset, the data set is about labeled users' reviews. I want to apply this to preprocessing of the dataset. Split the dataset into testing data and actual data, then input the data into the next stage which uses traditional techniques for word embedding and traditional classifiers as below. Apply on all Datasets TF-IDF and Random Forest Bag of Words and Random...dataset, the data set is about labeled users' reviews. I want to apply this to preprocessing of the dataset. Split the dataset into testing data and actual data, then input the data into the next stage which uses traditional techniques for word embedding and traditional classifiers as below. Apply on all Datasets TF-IDF and Random Forest Bag of Words and Random Forest TF-IDF and naive bayes Bag of Wo...

Naive people only write your proposal that are you free to start work now or not. Thank you.

I am looking to have some assistance predicting four out of six numbers correctly in a lottery using neural networks. I plan to use both training data and model predictions, and am also interested in employing more than one algorithm to accomplish the goal. In particul...looking to have some assistance predicting four out of six numbers correctly in a lottery using neural networks. I plan to use both training data and model predictions, and am also interested in employing more than one algorithm to accomplish the goal. In particular, I want to use neural networks as the main learning algorithm, but may also look into other options such as K-Nearest Neighbor and Naive Bayes. I'm looking for an experienced programmer with demonstrated knowledge in this field to help make this pro...

I am looking for an experienced freelancer to create a Machine Learning (ML) model in Python that can be used to accurately categorize text sentiment. Naive Bayes and n-grams algorithm are the algorithms needed for this project. The dataset for this project is provided. The plan is to evaluate about 13,000 utterances from 1433 dialogues from a TV series and characterize their multiparty dialogues into sentiments. The collected dialogues were categorized according to their dialogue length, i.e. the number of utterances in a dialogue, into four classes of which bucket length ranges are [5, 9], [10, 14], [15, 19], and [20, 24]. Finally, they randomly sampled 250 dialogues from each class to construct a dataset containing 1,000 dialogues. The data is labels with six basic emotions but...

...botnet traffic (classify botnet and normal traffic). The samples are labelled so just need the following: I need 2 files. The first file should use the following automated algorithms for feature selection: CFS ANOVA Chi-Squared The following supervised algorithms should be trained and tested. Decision Tree. Random Forest. Support Vector Machines (SVM). Bernoulli Naive Bayes. Ridge Classifier. Logistic Regression. Naive Bayes. K-nearest neighbors (KNN). The second file will allow me to select the features I want manually. The same algorithms should be used for training and testing. I then want both the results analysis to understand the difference in detection accuracy and they performed. For each file. I need the following: Heat map to show which feature correla...

My project is a spam classifier system built with a serverless platform and using a Naive Bayes algorithm. We are looking for an experienced developer to create the system using Python. The serverless platform will make the system highly scalable and cost-effective, while the Naive Bayes algorithm will maximize accuracy and speed in detecting potential spam. The engineer will be responsible for designing, building, and testing the system, using Python and any necessary third-party APIs to ensure proper functionality. Additionally, they must ensure that the system works seamlessly with the existing systems and data sources. We anticipate this project will take a minimum of two weeks to complete, depending on the complexity. As appropriate, the engineer must document their co...

I want to install google analytic conversion tracking on my website. I have tried to do this and I have some difficulties. I am not totally naive, but I have issues in testing whether my tracking code is working. I want someone who can screen share take me through the process and teach me how to do this conversion tracking. I am in Australia. I prefer the following Australian times 6 AM to 8 AM Monday to Friday 9 PM to 11 PM Monday to Friday 4 PM to 10 PM Saturday 6 AM to 10 PM Sunday Pick whatever suits you.

I would like to develop a simple game for young children/toddlers , possibly their first interaction with a touch screen. I imagine a farm-like static background with an Naive childish "Old McDonald" feel, which will be the first level in the game. I need a variety of animations where children can tap on a specific area of the image, and a fun animation will occur. For example, a tractor will start and smoke will come out of the chimney when children tap on it. I want all illustrations and animations to be child-friendly and enjoyable to look at. The necessary animated features include a lake, a barn, a farmer with a straw hat, a tractor, a cloud, a sun, a chimney, a bush, a sheep, a pig, and a cow. Some ideas for animations include fish jumping out of the lake, barn do...

...Complete the following: Split your data 80/20 for training test. Create at least four new columns. Build a naive Bayes classifier on the original training dataset and predict on the test set. Build a naive Bayes classifier on the training dataset with four new columns and predict on the test set. Using an appropriate error metric, which model is better? That is, did adding new features improve accuracy? 3. Complete the following: Using your modified training dataset i.e. the one with four new columns, perform two different feature selection approaches. Create two new training datasets that contain the five selected features according the the two different feature selection methods. Build a naive Bayes classifier on the two new training datasets and predict on the ...

Can you help me with redesigning our web dashboard? It is a document management tool having 4 components broadly 1) Document Storage 2) Document Generation 3) Settings 4) Sign up You can have a look at the mock designs at: It is designed by me, but as I am not a designer, the designs are really naive. The website is also live at where the document generation part is still not live. Can you please have a look and let me know if you would be interest to take up the task?

Project: React + ASP.NET Core The naive app first call a 3rd party API (HTTP), get JSON objects, then call backend rest API to save the data to database. The two APIs are correct. Please help fix the CORS Origin errors. You have to work remotely on my computer via TeamViewer. Thanks in advance!

you can use numpy, pandas ping me for more details

Please read the project description for full details. Need expert in k-fold cross validation, multinomial naive bayes, random forest and gradient boosted regression trees. Turnaround on this project is 24 hours but really need within 18 hours. Serious inquiries only.

we need naive Hausa translator

We want a set of very naive and simple drawing for the product of our website. It is an ice cream shop. the contest is for 5 products: -ice cream -Sunday (soft serve ice cream in a bowl with topping) -flurry (soft serve ice cream mixed with candy) -cold beverage (a slutch) -hot beverages (represent a coffee) I don't mind if you guys can find a stock illustration if we can pay the rights and use them. example of the type of image we are looking for is attached We need 5 images (or more) in png with transparent background.

we need naive Vietnamese translator

we need naive Vietnamese translator

...World of Machine Learning and Data Science. course can be completed by either doing Python tutorials, or R tutorials, or both - Python & R. Part 1 - Data Preprocessing Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression Part 3 - Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification Part 4 - Clustering: K-Means, Hierarchical Clustering Part 5 - Association Rule Learning: Apriori, Eclat Part 6 - Reinforcement Learning: Upper Confidence Bound, Thompson Sampling Part 7 - Natural Language Processing: Bag-of-words model and algorithms for NLP Part 8 - Deep Learning: Artificial Neural Network...