A high-quality supplier prediction method for building materials bidding platform
A forecasting method, supplier's technology, applied in forecasting, kernel method, neural learning method, etc., can solve problems such as sample imbalance, and achieve the effect of removing redundancy and high precision
Active Publication Date: 2021-05-14
筑客网络技术(上海)有限公司
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[0005] The technical problem to be solved by the present invention is to provide a high-quality supplier prediction method for the building materials bidding platform, which can effectively solve the problem of high-quality supplier prediction and the extremely unbalanced sample of new suppliers, and accurately locate high-quality suppliers for the platform business
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[0035] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.
[0036] The embodiment of the present invention relates to a high-quality supplier prediction method for a building material bidding platform. The method is based on the historical data of suppliers on the building material bidding platform, and learns the characteristics of high-quality suppliers from the data by a machine learning algorithm. mode, so as to accurately locate high-quality suppliers, such as figure 1 shown, incl...
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The invention relates to a high-quality supplier prediction method for a building materials bidding platform, comprising the following steps: dividing the suppliers into first suppliers and second suppliers according to the registration time length, and collecting the first supplier and the second supplier respectively. The attribute and behavior data of the supplier; use the XGBoost model to perform feature transformation on the behavior data of the first supplier to obtain an n-dimensional numbered vector, perform one-hot encoding on the n-dimensional numbered vector and splicing with the original features and input it into the logistic regression model for Prediction: perform evidence weight conversion on the behavior data of the second supplier, and calculate the IV value for feature dimension screening, and use a semi-supervised learning algorithm to predict; according to the high-quality suppliers among the first supplier and the second supplier Select the n suppliers with the highest predicted probability. The present invention can improve prediction accuracy.
Description
technical field [0001] The invention relates to the technical field of high-quality supplier prediction, in particular to a high-quality supplier prediction method for a building material bidding platform. Background technique [0002] Since the implementation of the "Electronic Bidding Measures" in 2013, various types of online trading platforms have sprung up like mushrooms after rain. The online bidding platform uses Internet technology to digitize the traditional offline bidding, bidding, bidding opening, bidding evaluation and winning bids, which greatly improves the bidding efficiency and simplifies the bidding process. [0003] Especially worthy of attention is the construction of online bidding platforms for domestic building materials procurement in recent years. After several years of extensive development, the major platforms have basically completed the initial accumulation of users such as building material procurement companies and supply companies. While the...
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IPC IPC(8): G06Q10/04G06N20/10G06N3/08
CPCG06N3/08G06Q10/04G06N20/10
Inventor 须峰黄麒铭李传中施海鹰李吉平
Owner 筑客网络技术(上海)有限公司