kaggle titanic

Ultraviolet A 11380-Down went the Titanic Question Link Give a picture with a thin ice on it '. 'or' * ', thick ice' @ ', wooden block' # '. At the beginning, people are on' * '. Thin Ice will sink only once, and the number of thick ice is unlimited, if a person is rescued after going to the block, but the size of a block is only P, how many people can be rescued? Idea: The maximum stream. Because there is a limit on the number of points, you can spli

People who have seen "Titanic" will never forget the "Ocean Heart (Heart of the Ocean)" necklace that slipped from the bottom of the heroine's finger to the end of the film, and she accompanied Rose for a lifetime, condensing the unforgettable memories. This example through the Photoshop Path tool and the layer style synthesis use, has created a romantic "The Ocean Heart" necklace, the operation is simple and practical, is suitable for the practice PS

April What is the most expected, that is to accompany the loved one to see Titanic together. Although Titanic's plot has let many audiences know by heart, but this 3DIMAX of the top technology, will give this beautiful heartbroken love has a brand-new audio-visual feast! Titanic Stills Gold Mountain Express to help you share in time As a titanic con

Using Python3 to learn the API of Decision tree classifierRelated to feature extraction, data type retention, classification type extraction of new typesNeed to download data sets online, I downloaded them to the local,can download code and datasets to my git: https://github.com/linyi0604/MachineLearning1 ImportPandas as PD2 fromSklearn.cross_validationImportTrain_test_split3 fromSklearn.feature_extractionImportDictvectorizer4 fromSklearn.treeImportDecisiontreeclassifier5 fromSklearn.metrics

multiple classification models in a certain order, the there is a dependency between them, and each subsequent model requires a comprehensive performance contribution from the existing model, - build a more powerful classifier from several weaker classifiers, such as a gradient-boosting decision tree - The decision tree of the prefect forest is set up to minimize the errors of the adult in fitting data. - + The following will compare the predictions of a decision tree with a single de

Maximum Flow, splitTest instructions: @ can walk infinitely, * person's initial position, others cannot walk. ~ Water, can't go, ... Can only walk once, #终点, can accommodate the number of p; Ask at most how many people were rescued (arrived #)This question is the biggest flow problem, mainly to build the diagram. How to build a diagram? Mainly with a split point, a point is split into two points, point (I,J) can be expressed as: Front point (i-1) *a+j, after the point (i-1) *a+j+m (m for a large

Input is disgusting.First the latitude and longitude of the time of the second conversion into degrees, and then according to things, south latitude to take the sign. Then according to the two-point distance formula of the ball.The final attention to the precision to take a larger#include POJ 2354 Titanic

some time ago with lineargradient ( linear gradient) write a color change flashing text control and text progress bar http://blog.csdn.net/huweigoodboy/article/details/43088953 , I recently saw an open source control on GitHub, Titanic, to analyze the effects such as:one, the realization principleyou need to use Bitmapshader to render the image with a picture. the picture above is a translucent half-white picture, and with the x-coordinate fluctuat

this include traversing time, time and machine, time fault, and spatial fault. Now let's explain the above phenomenon: 1. the sinking of Titanic, now you place yourself in the scene at that time, you find that sinking occurs between the ship and the surrounding scenes, between people and the sea, the atmosphere, the earth, and the surviving people, people's eyes show the things around them, and the plane of the sea can also see the reflection around

different passenger levels and survivalThe more advanced the class, the greater the proportion of survival. The proportion of those who were not rescued in class 3 was significantly increased. Indicates whether the class is related to the existence of the accommodation.The relationship between 3.2.2 Sex and survivalIt can be found that most are concentrated in the 20-50-year-old, from the box-line chart to see the average age of nearly 30 years.Because age is a continuous value, we consider the

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 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

training data contains a list of label and 784 column pixel values. The test data does not have a label column. Objective: To train the training data, to obtain the model and predict the label value of the test data.The following restores the picture from the pixel value to the actual picture, using Ipython notebook:In [1]:PwdC:\Users\zhaohf\DesktopIn [5]:CD .. / .. / .. / Workspace / Kaggle / Digitrecognizer / Data /C:\workspace\

This blog is based on Kaggle handwritten numeral recognition in combat as the goal, with KNN algorithm learning as the driving guidance to explain. The reason for writing this blog What is KNN The analysis of KNN Kaggle Combat Advantages and disadvantages and optimization methods Summarize Reference documents The reason for writing this blogMachine learning is very hot

Yesterday I downloaded a data set for handwritten numeral recognition in Kaggle, and wanted to train a model for handwritten digit recognition through some recent learning methods. These datasets are derived from 28x28 pixel-sized handwritten digital grayscale images, where the first element of the training data is a specific handwritten number, and the remaining 784 elements are grayscale values for each pixel of the handwritten digital grayscale ima

If the linear regression algorithm is like the Toyota Camry, then the gradient boost (GB) method is like the UH-60 Black Hawk helicopter. Xgboost algorithm as an implementation of GB is Kaggle machine learning competition victorious general. Unfortunately, many practitioners only use this algorithm as a black box (including the one I used to be). The purpose of this article is to introduce the principle of classical gradient lifting method intuitively

Kaggle, get up.Kaggle games rely on machines for automatic processing, and machine learning is almost a must-have skill. Getting Started with Kaggle the machine learning skills required is not in-depth, just need to have a basic understanding of the common methods of machine learning, for example, for a problem, you can realize that it is a classification problem AH or regression problem ah, Why the machine