xgboost: eXtreme Gradient Boosting
This is an introductory document of using the xgboost package in R. xgboost is short for eXtreme Gradient Boosting package. It is an efficient and scalable.
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Extreme gradient boosting (XGBoost) is a state-of-the-art machine learning model that performs well in processing both classification and regression tasks.
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Among the machine learning methods used in practice gradient tree boosting [10]1 is one technique that shines in many applications. Tree boosting has been
Bandwidth Control Mechanism and Extreme Gradient Boosting
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xgboost: Extreme Gradient Boosting
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EXTREME GRADIENT BOOSTING METHOD IN THE PREDICTION
EXTREME GRADIENT BOOSTING METHOD IN THE. PREDICTION OF COMPANY BANKRUPTCY. Barbara Pawe?ek1. ABSTRACT. Machine learning methods are increasingly being used
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xgboost: eXtreme Gradient Boosting
Jun 11 2020 This is an introductory document of using the xgboost package in R. xgboost is short for eXtreme Gradient Boosting package.
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EXTREME GRADIENT BOO
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Machine learning methods are increasingly being used to predict companyKey words:
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J4.8, linear discriminant analysis, linear support vector machine, logistic T k- k- homogeneity (in terms of financial condition assessment) of the set of companies Comparative studies carried out on selected methods to determine their suitabi7KHVWXG\E\=L
the compSTATISTICS IN TRANSITION new series,
157accuracy of the extreme gradient boosting method in predicting company
Table 1.
Ratio Description Ratio Description
W1 net profit / total assets W33 operating expenses / short-term liabilities W2 total liabilities / total assets W34 operating expenses / total liabilities W3 working capital / total assets W35 profit on sales / total assets W4 current assets / short-term liabilities W36 total sales / total assetsW5 [(cash + short-term securities +
receivables - short-term liabilities) / (operating expenses - depreciation)] * 365W37 (current assets - inventories) / long-
term liabilities W6 retained earnings / total assets W38 constant capital / total assets W7 EBIT / total assets W39 profit on sales / sales W8 book value of equity / total liabilities W40 (current assets - inventory - receivables) / short-term liabilities W9 sales / total assets W41 total liabilities / ((profit on operating activities + depreciation) * (12/365)) W10 equity / total assets W42 profit on operating activities / salesW11 (gross profit + extraordinary items +
financial expenses) / total assetsW43 rotation receivables + inventory
turnover in days W12 gross profit / short-term liabilities W44 (receivables * 365) / sales W13 (gross profit + depreciation) / sales W45 net profit / inventory W14 (gross profit + interest) / total assets W46 (current assets - inventory) / short- term liabilitiesW15 (total liabilities * 365) / (gross profit
+ depreciation)W47 (inventory * 365) / cost of products
soldW16 (gross profit + depreciation) / total
liabilitiesW48 EBITDA (profit on operating
activities - depreciation) / total assets158 :
Table 1.
Ratio Description Ratio Description
W17 total assets / total liabilities W49 EBITDA (profit on operating activities - depreciation) / sales W18 gross profit / total assets W50 current assets / total liabilities W19 gross profit / sales W51 short-term liabilities / total assets W20 (inventory * 365) / sales W52 (short-term liabilities * 365) / cost of products sold) W21 sales (n) / sales (n-1) W53 equity / fixed assetsW22 profit on operating activities / total
assetsW54 constant capital / fixed assets
W23 net profit / sales W55 working capital
W24 gross profit (in 3 years) / total
assetsW56 (sales - cost of products sold) /
sales W25 (equity - share capital) / total assets W57 (current assets - inventory - short-term liabilities) / (sales - gross profit - depreciation)W26 (net profit + depreciation) / total
liabilitiesW58 total costs / total sales
W27 profit on operating activities /
financial expensesW59 long-term liabilities / equity
W28 working capital / fixed assets W60 sales / inventory W29 logarithm of total assets W61 sales / receivables W30 (total liabilities - cash) / sales W62 (short-term liabilities *365) / sales W31 (gross profit + interest) / sales W63 sales / short-term liabilitiesW32 (current liabilities * 365) / cost of
products soldW64 sales / fixed assets
Source:
2. The data used in this study are derived from the Emerging MarketsSTATISTICS IN TRANSITION new series,
159rarely applied; this is due to the dynamic nat (2016), which adopted a time horizon of one to five years. Due to the fact that the 3.
The first step of our empirical research
2017error AUC Area under the ROC Curve. Once developed, the models were assessed in terms
Accuracy
Sensitivity
Specificity
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