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Kaggle competition-Otto Group Product Classification-simple solution to defeat half of participating teams, kaggle-otto

participating teams. Put the code on my github wepe/Kaggle-Solution, which can be divided into several parts:Data preprocessing Strictly speaking, I have not done much data preprocessing work. Only some functions that load data areLoadTrainSet () and loadTestSet (), load the training dataset and test dataset. The Code is as follows. Normalization and zero mean a

Kaggle Data Mining competition preliminary -- Titanic & lt; Data Transformation & gt;, kaggle -- titanic

Initial kaggle Data Mining Competition -- Titanic Full: https://github.com/cindycindyhi/kaggle-Titanic Feature Engineering Series: Raw data analysis and data processing in the Titanic Series Data Transformation of Titanic Series Derived attributes Dimension Reduction of Titanic Series After the missing value is filled, you need to process the attribute with other formats. For example, the values of the Se

Big Data competition platform--kaggle Getting Started

Big Data Competition Platform--kaggle Introductory articleThis article is suitable for those who just contact Kaggle, want to become familiar with Kaggle and finish a contest project independently, for the Netizen who has already competed on the Kaggle, can not spend time reading this article. This article is divided i

Machine Learning (a): Remember the study of K-one nearest neighbor algorithm and Kaggle combat

/DenominatorreturnNormdata#字符串数组转换整数defToInt (array): array=Mat (Array) m, n=Shape (Array) NewArray=Zeros ((M, N)) forIinch Range(m): forJinch Range(n): Newarray[i,j]= int(Array[i,j])returnNewArray#保存结果defSaveresult (RES): with Open(' Res.csv ',' W ', newline="') asFw:writer=Csv.writer (FW) Writer.writerows (RES)if __name__ == ' __main__ ': DataSet, labels=Loadtraindata () Testset=Loadtestdata () row=testset.shape[0]# Print ("

Kaggle Big Data Contest Platform Introduction

generous and the competition is relatively large; the competition shown for the study (yellow strips on the left) Less bonus; show as recruitment , although there is no bonus, but can be released to the project company internship/interview opportunities, which also gives the company to recruit talent another way. Shown as Playground for the practice race, Mainly used for beginner practiced hand, for beginners, it is recommended to start here . Getting Started inside to teach you step-by-step d

Tutorials | Kaggle Site Traffic Prediction Task first solution: from model to code detailed time series forecast

Https://mp.weixin.qq.com/s/JwRXBNmXBaQM2GK6BDRqMwSelected from GitHubArtur SuilinThe heart of the machine compilesParticipation: Shiyuan, Wall's, Huang Recently, Artur Suilin and other people released the Kaggle website Traffic Timing Prediction Contest first place detailed solution. They not only expose all the implementation code, but also explain the implementation model and experience in detail. The heart of the machine provides a brief o

"Kaggle" using random forest classification algorithm to solve biologial response problem

(such as sample size, shape and element composition, etc.) obtained by the molecule descriptor, the descriptor has been normalized.First time CommitThe game is a two-dollar classification problem whose data has been extracted and selected to make preprocessing easier, and although the game is over, you can still submit a solution so you can see comparisons with the world's best data scientists.Here, I use the random forest algorithm to train and predict, although the random forest is a more adv

The--digit of the Kaggle contest title recognizer

Classify handwritten digits using the famous MNIST dataThis competition was the first in a series of tutorial competitions designed to introduce people to machine learning.The goal-competition is-to-take an image of a handwritten a-digit, and determine what's digit is. As the competition progresses, we'll release tutorials which explain different machine learning algorithms To get started.The data for this competition were taken from the MNIST dataset

Dry Kaggle Popular | Solve all machine learning challenges with a single framework

New Smart Dollar recommendations  Source: LinkedIn  Abhishek Thakur  Translator: Ferguson  "New wisdom meta-reading" This is a popular Kaggle article published by data scientist Abhishek Thakur. The author summed up his experience in more than 100 machine learning competitions, mainly from the model framework to explain the machine learning process may encounter difficulties, and give their own solutions, he also listed his usual research database, al

Secret Kaggle Artifact Xgboost

. Vlad Mironov, Alexander Guschin, 1st place of the CERN LHCb experiment Flavour of Physics competition. Link to the Kaggle interview. how to apply. First to use Xgboost to do a simple two classification problem, the following data as an example, to determine whether the patient will abstainers diabetes in 5 years, the first 8 columns is a variable, the last column is the predicted value of 0 or 1. Data Description:Https://archive.ics.uci.edu/ml/data

Getting started with Kaggle-using Scikit-learn to solve digitrecognition problems

Getting started with Kaggle-using Scikit-learn to solve digitrecognition problems@author: Wepon@blog: http://blog.csdn.net/u0121626131, Scikit-learn simple introductionScikit-learn is an open-source machine learning toolkit based on NumPy, SciPy, and Matplotlib. Written in the Python language. Mainly covers classification,back and clustering algorithms such as KNN, SVM, logistic regression, Naive Bayes, random forest, K-means and many other algorithms

Get started with Kaggle -- use scikit-learn to solve DigitRecognition and scikitlearn

Get started with Kaggle -- use scikit-learn to solve DigitRecognition and scikitlearnGet started with Kaggle -- use scikit-learn to solve DigitRecognition Problems @ Author: wepon @ Blog: http://blog.csdn.net/u012162613 1. Introduction to scikit-learn Scikit-learn is an open-source machine learning toolkit based on NumPy, SciPy, and Matplotlib. It is written in Python and covers classification, Regression

"Python machine learning and Practice: from scratch to the road to the Kaggle race"

"Python Machine learning and practice – from scratch to the road to Kaggle race" very basicThe main introduction of Scikit-learn, incidentally introduced pandas, NumPy, Matplotlib, scipy.The code of this book is based on python2.x. But most can adapt to python3.5.x by modifying print ().The provided code uses Jupyter Notebook by default, and it is recommended to install ANACONDA3.The best is to https://www.kaggle.com registered account, run the fourth

Kaggle Invasive Species Detection VGG16 example--based on Keras

matplotlib.pyplot as Plt %matplot Lib inline trainpath = str (' e:\\kaggle\invasive_species\\train\\ ') testpath = str (' E:\\kaggle\\invasive_ Species\\test\\ ') n_tr = Len (Os.listdir (trainpath)) print (' num of training files: ', n_tr) Num of training files:2295 You can see the specifics of the train_labels.csv, which is shown in the table below, where the data is already scrambled, and the samples l

Kaggle Challenge Brief Introduction

Https://en.wikipedia.org/wiki/KaggleThe following, taken directly from Wikipedia, plays a role in recording, reminding yourself of the time to focus on the competition.Kaggle is a platform for predictive modelling and analytics competitions on which companies and researchers post Their data and statisticians and data miners from all over the world compete to produce the best models. This crowdsourcing approach relies on the fact that there is countless strategies that can is applied to any predi

What is the position of Kaggle in the MachineLearning field?

What kind of people will win the kaggle award? Can I learn something? Is it a highlight of job hunting or postgraduate application when I receive a prize at kaggle? What kind of people will win the kaggle award? Can I learn something? Is it a highlight of job hunting or postgraduate application when I receive a prize at kaggl

Remember a failed Kaggle match (3): Where the failure is, greedy screening features, cross-validation, blending

):%0.4f"% (I+1,nfold, Aucscore) Meanauc+=aucsco Re #print "mean AUC:%0.4f"% (meanauc/nfold) return meanauc/nfolddef greedyfeatureadd (CLF, data, label, SCO Retype= "accuracy", goodfeatures=[], maxfeanum=100, eps=0.00005): scorehistorys=[] While Len (Scorehistorys) In fact, there are a lot of things to say, but this article on this side, after all, a 1000+ people's preaching will make people feel bored, in the future to participate in other competitions together to say it.http://blog.kaggle.com/2

Using Theano to implement Kaggle handwriting recognition: Multilayer Perceptron

The previous blog introduced the use of the logistic regression to achieve kaggle handwriting recognition, this blog continues to introduce the use of multilayer perceptron to achieve handwriting recognition, and improve the accuracy rate. After I finished my last blog, I went to see some reptiles (not yet finished), so I had this blog after 40 days. Here, pandas is used to read the CSV file, the function is as follows. We used the first 8 parts of Tr

What is the status of Kaggle's game in the field of machine learning?

What kind of people can generally win prizes on the Kaggle? Can you learn something? is the award on Kaggle a bright spot for job seekers or graduate students? Reply content: A year or two after Netflix prize, this type of competition is beginning to prevail. The first ones to get a good grade are Daniel, Xiangliang, who was known as the second member of Netflix prize.In the past few years with the game mo

Identification of kaggle fish varieties

Kaggle Competition official website: https://www.kaggle.com/c/the-nature-conservancy-fisheries-monitoring Code: Https://github.com/pengpaiSH/Kaggle_NCFM Read reference: http://wh1te.me/index.php/2017/02/24/kaggle-ncfm-contest/ Related courses: http://course.fast.ai/index.html 1. Introduction to NCFM Image Classification task In order to protect and monitor the marine environment and ecological balance, The

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