卷积神经网络和随机森林的城市房价微观尺度制图方法
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姚尧, 任书良, 王君毅, 关庆锋
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Mapping the Fine-Scale Housing Price Distribution by Integrating a Convolutional Neural Network and Random Forest
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Yao YAO, Shuliang REN, Junyi WANG, Qingfeng GUAN
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表4 武汉中心区域不同地区房价的平均值、标准差和总体准确度 |
Tab. 4 Average values, standard deviations, and overall accuracies of housing prices in different districts in Wuhan central area |
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区域类别 | 区域 | 真实/(元/m2) | 预测/(元/m2) | 准确度/% | 平均值 | 标准差 | 平均值 | 标准差 | 主城区 | 江汉区 | 19 577.900 | 4612.090 | 19 261.333 | 3913.542 | 98.38 | 江岸区 | 20 845.530 | 7071.716 | 20 337.013 | 5188.628 | 97.56 | 洪山区 | 20 384.442 | 4577.304 | 19 654.007 | 3639.945 | 96.42 | 武昌区 | 22 129.308 | 6297.948 | 20 964.847 | 3467.340 | 94.74 | 汉阳区 | 16 674.734 | 3868.972 | 17 708.541 | 3544.656 | 93.80 | 青山区 | 15 822.054 | 4327.896 | 16 813.957 | 3255.780 | 93.73 | 远城区 | 江夏区 | 18 222.980 | 4833.506 | 18 423.225 | 3861.028 | 98.90 | 蔡甸区 | 15 347.774 | 4090.231 | 17 043.074 | 2801.621 | 88.95 | 东西湖区 | 14 127.650 | 3076.744 | 16 367.463 | 2822.753 | 84.15 | 黄陂区 | 12 825.273 | 2654.790 | 16 298.700 | 2303.813 | 72.92 |
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