Implementation scheme of intelligent risk control decision engine system
1. I ntroduction to risk control decision
The previous article realized the rule set and decision flow in the decision engine, and introduced the model engine and machine learning modeling. See the previous article for details:
Rule Engine Implementation Decision flow implementation Model engine implementation
In ...
Posted by zTagged on Sat, 02 Apr 2022 17:57:52 +0300
02 multivariate outlier detection
Step 0: clarify the task
Multivariate outlier detection (multivariate, outlier detection)Visual qualitative analysisQuantitative analysis and outlier handling
After completing all the work, we carried out backtracking and optimized the previous step:
I Define a general:
Specify the direction of the task (supervised / unsupervised / semi sup ...
Posted by norpel on Sat, 02 Apr 2022 09:13:50 +0300
Integrated learning manual
Punch in task
This punch in learning understands the three main tasks of machine learning, corresponding to the introduction of CH2 in the open source learning package, 1.1, 1.2 and 1.3
1. Introduction
What is machine learning, Machine learning can be regarded as a method of understanding data, discovering the laws in the data, analyzing ...
Posted by Brendan Nolan on Sat, 02 Apr 2022 06:01:42 +0300
[programming practice] select items
Topic source: Niuke, Alibaba programming question (2 stars), question 2
Title Description
Problem solution
Method 1: it's a crazy idea I think that the essence is to realize the addition of n-ary, but I think it is difficult to realize, so I use the binary conversion. Idea: take n=8, m=5 as an example. The minimum output (minn) must be & ...
Posted by darkknightgaury on Fri, 01 Apr 2022 19:21:54 +0300
Colab platform uses gensim package to realize Word2Vec and fasttext (cbow and skip gram)
It is not advisable to build wheels repeatedly. We should reasonably learn to adjust (tou) package (lan)!
Gensim is an open source library that can be used for unsupervised learning and natural language processing. The programming languages are Python and python. More details can be queried on the official website.
First import the basic pack ...
Posted by paolo on Thu, 31 Mar 2022 00:58:55 +0300
python computer vision - local image descriptor
The local image descriptor
Harris corner
corner points
The local window moves in all directions and produces obvious changesPoint of abrupt change in local curvature of image
Different types of corners
Corner detection algorithm
A good corner detection algorithm should have the following characteristics:
It can detect "real&quo ...
Posted by todayme on Wed, 30 Mar 2022 19:03:25 +0300
Using Python for age and gender detection, the results are funny
In this article, I will use Python programming language to take you through the task of using machine learning for age and gender detection. Age and gender detection is the task of computer vision, so I will use it
OpenCV Library in Python.
Before starting the task of using Python for age and gender detection, I will first take you to underst ...
Posted by deep on Sun, 27 Mar 2022 04:50:46 +0300
Deep learning classic network analysis: DenseNet
1. Background introduction
DenseNet is CVPR's Best Paper in 2017. It breaks away from the stereotype of deepening the number of network layers (ResNet) and widening the network structure (Inception) to improve the network performance. From the perspective of features, through feature reuse and bypass setting, it not only great ...
Posted by MattG on Sun, 27 Mar 2022 04:05:43 +0300
Data mining -- HeartbeatClassification
Task 5: model fusion
Model fusion is an important link in the later stage of the competition. There are roughly the following ways:
Simple weighted fusion Regression (classification probability): Arithmetic mean, Geometric mean; Category: voting Synthesis: rank averaging, log mergingstacking/blending Build a multi-layer model, and use the pre ...
Posted by McJepp on Sat, 26 Mar 2022 18:32:18 +0300
(Tianchi) zero foundation introduction data mining - Summary notes of heartbeat signal classification and prediction
1. Simple linear weighted fusion
import numpy as np
import pandas as pd
from sklearn import metrics
## Generate some simple sample data, test_prei represents the predicted value of the ith model
test_pre1 = [1.2, 3.2, 2.1, 6.2]
test_pre2 = [0.9, 3.1, 2.0, 5.9]
test_pre3 = [1.1, 2.9, 2.2, 6.0]
# y_test_true represents the true value of the se ...
Posted by jeicrash on Sat, 26 Mar 2022 11:41:48 +0300