[hands on data analysis] Task05 - model establishment and evaluation

Basic process of modeling and evaluation: Zero, characteristic Engineering Import data: import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt from IPython.display import Image plt.rcParams['font.sans-serif'] = ['SimHei'] # Used to display Chinese labels normally plt.rcParams['axes.unicode_minus'] ...

Posted on Thu, 23 Sep 2021 08:10:50 -0400 by jOE :D

How to deal with missing values in machine learning

How to deal with missing values in machine learning Note: this data is from kaggle, please stamp for details here , original reference connection, please stamp here , this paper is a long one, which aims to introduce some ideas and details in the process of EDA. 1, Introduction The purpose of this EDA(Exploratory Data Analysis) is ...

Posted on Thu, 23 Sep 2021 05:58:16 -0400 by g00bster

BP neural network and its application [neural network iv]

Typical case analysis of BP neural network [example 5-1] 60 groups of gasoline samples were scanned by Fourier near infrared transform spectrometer. The scanning range was 900 ~ 1700nm and the scanning interval was 2nm. The spectral curve of each sample contained 401 wavelength points. At the same time, the octane number content was determined ...

Posted on Thu, 23 Sep 2021 03:35:19 -0400 by northernmonkey

Data analysis and mining 3 - Feature Engineering

Data and features determine the upper limit of machine learning, and models and algorithms only approximate this upper limit 1. Data preprocessing data acquisitionData cleaning: remove dirty dataData sampling: it can be used when the data is unbalanced, including up sampling and down sampling; Positive sample > negative sample, and the amo ...

Posted on Tue, 21 Sep 2021 18:16:19 -0400 by little_webspinner

Human words explain linear regression and gradient descent

from sklearn.datasets import load_boston from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.linear_model import LinearRegression from sklearn.metrics import mean_squared_error from sklearn.linear_model import SGDRegressor import pandas as pd def linear_model(): # get data ...

Posted on Tue, 21 Sep 2021 16:58:37 -0400 by xwishmasterx

Point cloud segmentation based on logo-beam analysis

Reprint address: https://zhuanlan.zhihu.com/p/382460472 Logo-beam is a laser radar SLAM algorithm. The corresponding paper is "logo-beam: light and ground optimized lidar odometry and mapping on variable terrain", with open source code. Next, we will make a simple analysis of logo-logo in combination with the paper and code. Logo-log ...

Posted on Tue, 21 Sep 2021 15:39:05 -0400 by pure_skill_2000

From Dutch Flag Issue to Fast Row Optimized Upgrade

If there is a skill in the field of computers that will remain obsolete after ten or twenty years, I think it must be algorithms and data structures. I. The Dutch Flag                  The so-called Dutch flag problem is that given a set of numbers, put the number less than a certain number of nums on the left, the number equal to num in the ...

Posted on Tue, 21 Sep 2021 12:06:16 -0400 by mudasir

[numerical calculation-19]: numerical derivative method of universal arbitrary function

Author home page( Silicon based workshop of slow fire rock sugar): Slow fire rock sugar (Wang Wenbing) blog silicon based workshop of slow fire rock sugar _csdnblog Website of this article: https://blog.csdn.net/HiWangWenBing/article/details/120378620 catalogue Chapter 1 Preface Chapter 2 numerical definition of derivative Chapter 3 numer ...

Posted on Tue, 21 Sep 2021 02:47:55 -0400 by robin

In the absence of data, Bayesian theorem is used to design knowledge driven model

Without data but with expert knowledge, knowledge can also be transformed into computer-aided model. Data is the basis of the model, but without data, only domain experts can well describe or even predict the "situation" of a given environment. I will summarize the concept of knowledge driven model based on Bayesian probability, and ...

Posted on Tue, 21 Sep 2021 02:25:12 -0400 by meritre

PyTorch pit six data processing modules Dataloader and Dataset

Overview of data processing in deep learning Three elements of deep learning: data, computing power and algorithm In engineering practice, the importance of data has attracted more and more attention. In the data science community, there is a saying that "data determines the upper limit of the model, and algorithm determines the lower lim ...

Posted on Mon, 20 Sep 2021 21:38:27 -0400 by ven.ganeva