#r
#r
Вопрос:
У меня есть фрейм данных, который указывает дорогу type , и 24 столбца ( h_1 ... h_24 ), которые показывают, сколько транспортных средств проезжает (относительно за день) в час. Каждый ряд — это отдельная дорога.
Мне интересно найти общие черты между типами. Мой предполагаемый результат — это объединение типов дорог. Т.е. Типы дорог 2 и 3, по-видимому, имеют одинаковый шаблон, поэтому они группируются в новую категорию (например category , ).
Итак, мой вопрос в том, как можно обнаружить такого рода паттерны с помощью целых 15 различных типов?
Часть моих данных:
structure(list(type = c(14, 14, 11, 4, 13, 12, 13, 13, 13, 13,
11, 14, 1, 11, 14, 11, 4, 13, 14, 9, 14, 13, 13, 9, 14, 13, 1,
11, 14, 13, 13, 13, 11, 13, 15, 11, 14, 11, 14, 13, 9, 11, 13,
9, 14, 13, 13, 13, 13, 13, 9, 14, 13, 12, 11, 14, 11, 4, 11,
4, 13, 9, 13, 9, 13, 13, 1, 15, 1, 6, 13, 11, 13, 6, 11, 11,
11, 13, 13, 13, 12, 13, 14, 13, 11, 9, 14, 11, 13, 11, 3, 11,
11, 11, 14, 11, 13, 14, 13, 11, 11, 14, 11, 11, 13, 15, 12, 11,
4, 13, 14, 13, 11, 13, 14, 11, 9, 13, 13, 11, 11, 11, 13, 11,
11, 13, 13, 13, 14, 11, 9, 11, 13, 4, 12, 13, 13, 9, 13, 11,
13, 11, 13, 1, 9, 13, 11, 11, 13, 11), h_1 = c(1.091, 0.591,
1.129, 0.274, 0.178, 1.507, 0.654, 1.003, 0.228, 0.657, 1.411,
0.97, 0.875, 0.397, 1.462, 1.063, 0.648, 1.181, 0.629, 1.219,
2.193, 1.054, 0.768, 0.922, 1.525, 2.891, 0.888, 1.171, 0.684,
0.455, 0.562, 1.138, 0.895, 0.71, 0.445, 1.444, 3.644, 2.365,
0.391, 0.687, 1.037, 0.423, 2.14, 0.942, 1.33, 0.737, 1.766,
0.144, 1.08, 0.672, 0.629, 0.39, 0.325, 1.079, 2.099, 0.163,
0.871, 1.112, 1.731, 0.313, 1.039, 1.057, 1.159, 0.959, 0.755,
0.741, 0.429, 1.017, 0.602, 0.359, 0.574, 0.872, 0.639, 0.786,
0.857, 1.212, 2.553, 1.755, 0.543, 1.691, 0.715, 0.352, 1.431,
1.188, 2.115, 0.536, 0.605, 0.894, 0.745, 2.639, 0.545, 1.135,
0.702, 0.82, 0.462, 0.263, 1.362, 0.226, 0.801, 1.783, 1.301,
1.024, 1.394, 1.512, 1.151, 4.175, 0.644, 2.11, 0.518, 1.938,
1.048, 0.942, 1.233, 1.024, 1.967, 1.601, 0.736, 0.496, 1.346,
1.109, 0.78, 0.635, 0.567, 0.378, 2.976, 0.453, 0.392, 1.362,
1.042, 0.555, 1.218, 0.936, 1.098, 0.868, 1.172, 0.247, 1.287,
0.824, 1.025, 0.863, 1.484, 0.507, 1.335, 0.637, 1.986, 1.137,
0.837, 1.787, 0.353, 1.865), h_2 = c(0.607, 0.284, 0.753, 0.164,
0.085, 1.046, 0.422, 0.816, 0.1, 0.445, 1.032, 0.559, 0.699,
0.334, 1.092, 0.544, 0.494, 0.803, 0.251, 0.862, 2.53, 1.389,
0.705, 0.382, 0.932, 2.332, 0.604, 0.801, 0.329, 0.248, 0.411,
0.866, 0.584, 0.295, 0.26, 0.873, 2.943, 1.887, 0.287, 0.462,
0.668, 0.411, 2.101, 0.636, 0.88, 0.389, 1.24, 0.072, 0.804,
0.481, 0.346, 0.194, 0.093, 0.629, 1.644, 0.122, 0.615, 0.604,
1.308, 0.25, 0.577, 0.996, 0.849, 0.594, 0.418, 0.452, 0.252,
0.706, 0.348, 0.16, 0.297, 0.608, 0.57, 0.413, 0.745, 0.839,
1.894, 1.315, 0.344, 1.046, 0.35, 0.206, 0.987, 0.422, 1.595,
0.229, 0.263, 0.501, 0.556, 2.112, 0.303, 0.765, 0.485, 0.517,
0.24, 0.11, 0.88, 0.104, 0.649, 1.198, 0.948, 0.708, 0.917, 0.729,
0.743, 3.336, 0.35, 1.635, 0.253, 1.421, 0.539, 0.554, 0.82,
0.708, 1.411, 1.011, 0.638, 0.297, 0.918, 0.427, 0.676, 0.449,
0.556, 0.401, 2.192, 0.194, 0.264, 0.879, 0.667, 0.319, 0.854,
0.613, 0.683, 0.481, 0.855, 0.305, 0.865, 0.593, 0.568, 0.552,
1.002, 0.314, 0.953, 0.341, 1.415, 0.508, 0.441, 1.18, 0.24,
1.277), h_3 = c(0.505, 0.171, 0.277, 0.164, 0.097, 0.774, 0.305,
0.646, 0.132, 0.416, 0.853, 0.412, 0.621, 0.508, 0.8, 0.336,
0.432, 0.667, 0.163, 0.7, 2.953, 0.383, 0.656, 0.161, 0.635,
0.551, 0.466, 0.295, 0.229, 0.217, 0.141, 1.002, 0.498, 0.138,
0.177, 0.531, 1.688, 1.634, 0.259, 0.472, 0.565, 0.42, 2.051,
0.488, 0.703, 0.202, 1.03, 0.072, 0.603, 0.552, 0.208, 0.122,
0.023, 0.419, 1.278, 0.081, 0.54, 0.397, 0.921, 0.188, 0.357,
1.049, 0.602, 0.431, 0.193, 0.191, 0.204, 0.452, 0.3, 0.1, 0.173,
0.216, 0.531, 0.28, 0.772, 0.307, 1.486, 0.994, 0.164, 0.681,
0.229, 0.222, 0.723, 0.134, 1.217, 0.189, 0.152, 0.205, 0.562,
1.579, 0.242, 0.114, 0.434, 0.401, 0.218, 0.07, 0.645, 0.111,
0.604, 0.876, 0.847, 0.603, 0.797, 0.573, 0.464, 2.183, 0.266,
1.08, 0.161, 1.034, 0.342, 0.43, 0.533, 0.603, 1.064, 0.601,
0.731, 0.24, 0.801, 0.173, 0.192, 0.141, 0.522, 0.435, 1.044,
0.129, 0.226, 0.64, 0.502, 0.113, 0.466, 0.54, 0.523, 0.283,
0.697, 0.321, 0.701, 0.461, 0.358, 0.403, 0.828, 0.151, 0.662,
0.272, 0.997, 0.28, 0.195, 0.611, 0.353, 1.027), h_4 = c(0.366,
0.166, 0.218, 0.206, 0.047, 0.625, 0.333, 0.685, 0.691, 0.739,
0.937, 0.397, 0.739, 0.703, 0.737, 0.304, 0.432, 0.621, 0.163,
0.774, 2.831, 0.101, 0.929, 0.153, 0.466, 0.186, 0.454, 0.218,
0.331, 0.302, 0.105, 2.127, 0.638, 0.188, 0.264, 0.548, 1.327,
1.387, 0.394, 0.791, 0.614, 0.639, 1.671, 0.496, 1.185, 0.179,
1.192, 0.287, 0.779, 0.844, 0.265, 0.187, 0.023, 0.383, 1.169,
0.122, 0.764, 0.334, 0.835, 0.188, 0.367, 1.277, 0.799, 0.414,
0.193, 0.245, 0.3, 0.367, 0.363, 0.2, 0.254, 0.167, 0.574, 0.186,
1.166, 0.221, 1.512, 0.832, 0.161, 0.714, 0.326, 0.416, 0.867,
0.23, 1.107, 0.348, 0.218, 0.179, 0.935, 1.295, 0.262, 0.177,
0.823, 0.472, 0.295, 0.116, 0.717, 0.271, 0.791, 0.958, 1.371,
0.744, 0.968, 0.706, 0.409, 1.466, 0.249, 0.912, 0.207, 0.827,
0.332, 0.359, 0.702, 0.744, 0.859, 0.544, 0.993, 0.357, 1.109,
0.218, 0.299, 0.144, 0.558, 1.027, 0.761, 0.172, 0.349, 0.719,
0.664, 0.18, 0.406, 0.777, 0.541, 0.274, 0.918, 1.109, 0.675,
0.522, 0.321, 0.489, 0.828, 0.085, 0.57, 0.351, 0.823, 0.134,
0.215, 0.559, 0.396, 1.172), h_5 = c(0.759, 0.362, 0.394, 1.041,
0.08, 0.598, 0.714, 0.738, 4.113, 1.674, 0.948, 0.661, 1.051,
2.606, 0.996, 0.462, 0.571, 1.056, 0.415, 1.242, 2.291, 0.096,
1.211, 0.288, 0.593, 0.727, 0.721, 0.305, 0.967, 0.687, 0.257,
4.004, 1.267, 0.381, 0.628, 0.813, 1.521, 1.281, 0.925, 1.738,
0.872, 2.14, 1.936, 0.698, 1.752, 0.29, 2.07, 0.647, 1.381, 1.377,
0.531, 0.514, 0.162, 0.408, 1.346, 0.448, 2.163, 0.429, 0.907,
0.563, 0.499, 2.062, 1.532, 0.572, 0.396, 0.52, 0.754, 0.537,
0.714, 0.819, 0.821, 0.255, 0.836, 0.266, 2.112, 0.313, 2.199,
0.796, 0.367, 1.3, 0.544, 1.199, 1.131, 0.23, 1.134, 1.306, 0.417,
0.199, 1.416, 1.598, 0.545, 0.3, 2.043, 0.963, 0.652, 0.354,
1.26, 0.793, 1.481, 1.838, 3.07, 1.419, 1.634, 0.932, 0.39, 1.545,
0.701, 1.102, 0.46, 0.887, 0.585, 0.543, 0.999, 1.419, 1.107,
0.623, 1.456, 0.56, 1.963, 0.231, 0.439, 0.162, 0.784, 2.901,
1.314, 0.323, 0.847, 1.264, 1.313, 0.417, 0.78, 1.9, 0.857, 0.538,
1.647, 2.558, 1.153, 0.768, 0.568, 0.91, 1.421, 0.237, 0.755,
0.832, 1.183, 0.107, 0.491, 1.175, 0.848, 2.117), h_6 = c(1.836,
0.961, 1.605, 3.069, 0.089, 1.005, 2.508, 1.717, 5.413, 4.381,
1.665, 1.441, 1.89, 6.892, 2.116, 1.612, 1.157, 2.141, 1.571,
3.35, 2.667, 0.718, 1.845, 0.978, 1.186, 1.787, 1.974, 1.03,
2.14, 1.405, 1.073, 5.952, 3.467, 1.101, 1.578, 2.122, 2.36,
1.302, 2.865, 3.508, 1.718, 4.415, 2.705, 1.552, 3.541, 0.97,
3.108, 0.862, 3.365, 2.782, 1.806, 1.757, 2.921, 0.752, 2.146,
0.855, 4.545, 0.683, 1.447, 1.939, 1.292, 3.794, 3.581, 1.262,
1.564, 1.683, 3.417, 0.65, 1.804, 2.016, 2.446, 0.702, 1.869,
0.746, 3.343, 1.033, 3.984, 1.067, 1.434, 2.076, 2.226, 4.295,
2.023, 1.016, 1.737, 3.669, 1.225, 0.485, 2.42, 3.062, 1.736,
1.372, 3.244, 2.885, 1.806, 2.403, 2.771, 1.791, 2.834, 3.889,
4.502, 2.807, 3.486, 2.375, 0.817, 1.847, 2.197, 2.185, 1.645,
1.362, 1.48, 1.149, 1.788, 2.807, 2.003, 0.997, 2.618, 1.616,
3.618, 1.369, 1.354, 0.5, 2.065, 4.543, 2.877, 1.271, 2.494,
2.778, 3.167, 1.745, 2.359, 4.095, 1.943, 1.415, 3.547, 5.202,
2.58, 1.96, 1.124, 3.238, 3.02, 1.367, 1.726, 2.302, 2.512, 0.759,
2.192, 3.15, 2.839, 4), h_7 = c(3.944, 2.971, 3.597, 7.331, 0.157,
3.246, 5.143, 4.038, 4.62, 8.276, 3.273, 4.792, 4.084, 7.116,
5.171, 4.521, 4.489, 3.858, 4.978, 4.881, 5.335, 1.361, 3.734,
2.205, 3.643, 3.594, 3.541, 2.524, 4.838, 4.157, 2.983, 6.644,
7.517, 2.41, 4.247, 5.508, 4.549, 2.551, 6.072, 6.069, 2.842,
5.862, 5.345, 3, 4.769, 2.266, 4.495, 1.15, 6.454, 4.976, 5.955,
6.088, 4.59, 2.782, 4.862, 2.28, 5.885, 2.574, 3.431, 4.878,
5.899, 5.832, 5.674, 3.591, 3.531, 4.825, 7.777, 2.232, 5.971,
6.209, 5.998, 2.159, 4.549, 2.784, 4.631, 2.271, 5.291, 3.231,
3.554, 4.512, 5.732, 8.902, 3.408, 3.22, 3.883, 6.306, 2.911,
1.414, 4.128, 3.826, 5.774, 2.821, 5.404, 5.808, 5.438, 5.799,
4.229, 4.481, 4.958, 5.625, 5.415, 4.743, 5.998, 4.464, 2.284,
3.182, 6.053, 4.695, 6.305, 3.106, 2.605, 2.989, 4.678, 4.743,
4.143, 2.808, 4.523, 4.027, 4.915, 5.688, 2.799, 1.262, 4.947,
5.731, 5.335, 3.685, 5.917, 4.241, 7.878, 3.28, 5.54, 4.96, 5.138,
4.028, 6.175, 7.239, 4.571, 4.087, 3.57, 5.434, 4.19, 3.716,
3.671, 7.065, 4.635, 1.697, 4.962, 4.667, 4.746, 4.848), h_8 = c(5.215,
5.386, 6.699, 8.865, 0.427, 5.445, 7.39, 6.853, 6.185, 7.8, 5.74,
6.424, 6.53, 7.32, 6.008, 8.395, 10.026, 4.249, 8.699, 5.004,
6.313, 2.168, 7.191, 5.241, 5.125, 5.37, 5.069, 4.746, 6.941,
7.316, 6.779, 6.306, 7.13, 4.673, 7.553, 6.066, 5.055, 4.024,
8.355, 6.071, 3.719, 6.783, 7.185, 3.995, 5.642, 4.749, 5.131,
1.833, 6.354, 6.263, 7.299, 8.336, 6.351, 4.624, 5.835, 4.439,
5.088, 4.1, 5.431, 4.44, 7.039, 6.247, 5.87, 5.735, 6.145, 6.091,
7.619, 6.102, 8.134, 6.349, 8.065, 5.498, 6.431, 4.169, 5.304,
4.546, 5.721, 5.607, 7.894, 6.478, 7.121, 7.671, 4.972, 5.923,
4.956, 7.251, 5.109, 4.452, 6.651, 4.112, 6.743, 5.306, 5.581,
6.09, 8.751, 10.775, 4.649, 6.467, 6.948, 5.593, 5.717, 5.431,
6.158, 5.759, 3.807, 3.975, 6.76, 5.866, 7.375, 4.356, 4.117,
4.146, 7.317, 5.431, 6.002, 4.177, 5.432, 6.185, 5.164, 8.952,
4.595, 3.218, 6.032, 5.805, 5.246, 4.59, 8.141, 4.648, 8.084,
6.147, 5.986, 4.995, 6.718, 4.528, 8.55, 8.742, 5.106, 6.335,
4.793, 5.607, 4.527, 9.264, 5.148, 7.653, 5.048, 3.544, 6.039,
5.443, 5.538, 4.979), h_9 = c(5.279, 5.904, 7.211, 6.111, 0.686,
5.486, 6.411, 7.185, 7.688, 5.984, 5.925, 5.703, 6.011, 6.917,
5.155, 6.805, 9.44, 4.454, 7.568, 4.831, 5.196, 1.964, 7.191,
4.502, 4.701, 4.84, 5.185, 4.929, 7.045, 7.729, 6.769, 5.887,
5.477, 5.668, 7.034, 6.077, 4.772, 4.451, 7.419, 6.329, 4.182,
6.222, 6.138, 4.144, 6.23, 4.38, 5.154, 2.3, 6.404, 5.772, 5.932,
7.208, 7.626, 4.986, 5.043, 8.145, 5.184, 4.195, 5.652, 4.941,
5.91, 5.384, 5.672, 6.187, 5.849, 6.842, 5.453, 7.599, 6.645,
4.831, 8.056, 5.92, 6.229, 4.236, 5.425, 4.728, 5.045, 5.764,
9.408, 6.174, 6.258, 6.956, 5.795, 6.728, 4.565, 6.555, 5.895,
4.633, 7.259, 4.601, 5.855, 5.48, 5.246, 5.448, 7.517, 9.931,
4.938, 6.758, 6.838, 4.945, 5.694, 5.569, 5.11, 5.72, 4.327,
4.316, 6.338, 5.586, 6.627, 4.62, 5.437, 5.406, 6.071, 5.569,
4.98, 4.102, 5.439, 7.023, 5.06, 6.871, 5.272, 3.925, 6.269,
5.077, 4.981, 4.224, 6.76, 4.936, 7.325, 6.029, 5.669, 5.122,
6.133, 4.009, 8.74, 8.375, 4.909, 5.907, 4.212, 5.546, 4.625,
9.848, 5.362, 6.648, 4.422, 3.788, 6.14, 5.741, 5.806, 5.027),
h_10 = c(5.058, 6.346, 6.55, 5.07, 1.484, 5.323, 5.278, 5.735,
6.742, 5.904, 5.429, 5.483, 5.835, 6.039, 4.841, 5.971, 6.849,
5.019, 5.946, 5.286, 4.46, 2.251, 5.69, 4.145, 4.659, 4.651,
4.937, 4.407, 6.683, 8.145, 6.157, 5.74, 5.485, 6.393, 7.573,
6.145, 4.81, 4.735, 5.986, 6.048, 4.754, 6.089, 5.299, 4.212,
5.896, 4.195, 5.432, 4.06, 5.801, 4.853, 5.505, 6.439, 8.785,
5.16, 4.865, 5.701, 6.12, 4.608, 5.585, 5.691, 5.775, 5.481,
5.769, 5.989, 5.114, 6.312, 4.829, 5.96, 5.713, 4.073, 6.565,
4.873, 5.742, 5.089, 5.368, 4.296, 4.905, 5.46, 6.302, 6.095,
5.621, 6.09, 5.853, 6.594, 4.785, 5.915, 6.814, 4.733, 7.454,
4.967, 6.562, 5.022, 5.416, 5.736, 6.562, 7.703, 5.361, 7.068,
5.823, 5.008, 5.717, 6.034, 5.176, 5.567, 4.828, 4.853, 5.759,
5.522, 6.224, 5.135, 6.105, 6.028, 5.328, 6.034, 5.202, 4.424,
5.67, 5.98, 5.371, 5.011, 5.106, 4.307, 6.163, 5.434, 5.086,
4.31, 5.25, 5.36, 5.911, 5.119, 5.45, 5.3, 5.851, 4.142,
5.795, 5.223, 5.202, 4.818, 4.274, 5.377, 5.083, 7.644, 5.714,
5.638, 4.582, 4.417, 6.002, 5.24, 6.413, 5.264), h_11 = c(5.189,
7.161, 6.16, 5.029, 3.229, 5.663, 5.523, 6.22, 5.834, 5.981,
5.588, 5.924, 6.1, 5.593, 5.359, 5.823, 5.877, 5.658, 6.034,
5.53, 4.847, 3.975, 5.727, 4.918, 5.083, 5.428, 5.219, 4.19,
6.593, 8.498, 5.693, 5.474, 5.866, 7.03, 7.822, 6.103, 4.899,
5.251, 5.579, 5.878, 5.56, 6.383, 5.226, 4.756, 6.012, 4.302,
5.936, 3.881, 5.65, 4.818, 5.626, 6.501, 4.288, 5.74, 5.171,
6.108, 6.609, 5.514, 5.815, 7.067, 5.748, 5.871, 6.02, 6.103,
5.188, 6.302, 4.994, 6.102, 5.514, 4.232, 4.934, 4.352, 5.851,
6.021, 5.562, 3.678, 5.036, 5.673, 4.629, 6.192, 5.913, 5.603,
5.916, 7.591, 5.181, 5.692, 7.577, 5.298, 7.374, 5.33, 6.885,
5.202, 5.675, 6.281, 6.411, 5.672, 5.839, 7.519, 6.107, 5.004,
6.014, 6.47, 5.543, 5.677, 5.682, 5.023, 6.043, 5.651, 6.42,
5.696, 6.552, 6.117, 5.337, 6.47, 5.716, 5.585, 6.013, 5.962,
5.692, 4.826, 6.334, 6.454, 6.221, 5.687, 5.396, 5.452, 5.035,
5.838, 5.372, 4.676, 5.881, 5.53, 5.994, 5.085, 4.497, 4.996,
5.709, 4.862, 5.015, 5.277, 5.425, 6.354, 6.517, 5.427, 5.353,
5.554, 5.542, 5.476, 7.077, 5.483), h_12 = c(6.006, 7.094,
5.992, 4.892, 5.527, 5.758, 5.853, 6.067, 5.441, 5.388, 5.872,
6.497, 6.347, 5.749, 5.449, 5.799, 5.769, 5.261, 6.084, 5.822,
4.877, 2.203, 6.523, 6.14, 5.972, 5.421, 5.607, 4.782, 6.095,
8.027, 5.084, 5.227, 5.285, 7.219, 8.326, 5.96, 4.82, 5.55,
5.881, 5.624, 6.303, 6.584, 5.299, 5.366, 7.179, 4.949, 5.607,
5.102, 5.977, 5.271, 5.926, 6.274, 5.239, 6.359, 5.375, 6.231,
6.533, 6.817, 5.978, 6.754, 5.845, 6.12, 5.96, 6.148, 5.58,
6.066, 5.093, 6.271, 5.443, 5.151, 5.033, 5.141, 6.123, 6.887,
5.763, 4.457, 4.872, 5.669, 4.608, 6.125, 6.323, 5.127, 6.01,
5.655, 5.62, 6.021, 7.806, 5.97, 6.284, 5.317, 6.945, 5.344,
5.857, 5.594, 6.486, 5.019, 5.764, 7.185, 6.517, 4.913, 5.67,
6.085, 5.197, 5.733, 6.351, 4.874, 5.961, 5.461, 6.546, 6.145,
7.203, 6.776, 5.585, 6.085, 5.576, 6.505, 6.235, 6.488, 5.459,
5.14, 5.987, 6.034, 6.521, 6.028, 5.297, 6.444, 5.302, 5.763,
5.304, 5.01, 6.146, 5.496, 6.166, 5.821, 5.193, 5.692, 5.393,
5.274, 5.633, 5.832, 5.267, 6.054, 6.359, 5.537, 5.942, 5.417,
5.874, 5.397, 6.357, 5.321), h_13 = c(6.382, 7.456, 5.787,
5.111, 8.092, 5.445, 5.874, 6.724, 5.643, 5.912, 5.375, 5.762,
6.451, 5.818, 5.291, 5.136, 5.244, 5.707, 5.607, 6.193, 4.612,
3.928, 6.428, 8.983, 6.057, 6.555, 6.157, 5.853, 6.179, 5.981,
4.841, 5.41, 5.753, 7, 8.053, 5.501, 4.74, 4.947, 6.016,
5.256, 6.574, 6.457, 4.814, 6.047, 7.346, 5.871, 5.659, 7.654,
5.198, 5.101, 5.81, 5.447, 4.822, 6.117, 4.999, 6.068, 6.337,
6.293, 5.421, 6.567, 5.83, 6.171, 5.885, 6.25, 6.075, 6.12,
4.863, 5.763, 5.438, 5.849, 5.203, 6.08, 6.343, 6.008, 6.01,
5.84, 4.99, 5.15, 4.9, 5.82, 5.972, 4.861, 5.949, 4.792,
5.057, 6.005, 7.517, 6.63, 5.745, 5.071, 6.42, 5.11, 5.905,
6.089, 6.229, 4.908, 5.724, 6.269, 6.566, 5.418, 5.983, 6.295,
5.578, 5.634, 6.518, 4.916, 5.878, 5.115, 6.017, 5.491, 6.706,
6.965, 5.24, 6.295, 5.458, 6.077, 6.325, 6.684, 5.684, 5.056,
5.306, 6.174, 6.427, 5.738, 4.824, 6.271, 5.476, 5.723, 4.761,
5.836, 5.52, 5.633, 5.515, 5.849, 4.908, 5.357, 5.863, 5.775,
5.497, 6.402, 5.548, 5.791, 5.729, 5.537, 5.428, 5.091, 6.287,
4.913, 6.385, 5.436), h_14 = c(6.865, 5.34, 5.906, 6.166,
9.527, 6.315, 6.553, 6.379, 6.105, 6.025, 6.292, 6.424, 6.883,
6.203, 5.484, 6.954, 6.694, 6.35, 6.6, 6.346, 4.679, 6.227,
6.058, 6.076, 5.972, 6.76, 6.654, 6.336, 5.184, 5.248, 5.422,
5.054, 5.889, 4.89, 5.566, 6.149, 5.025, 5.514, 7.41, 4.755,
6.912, 6.719, 5.293, 6.723, 6.496, 6.209, 5.786, 8.121, 5.55,
5.609, 6.491, 4.488, 5.447, 6.319, 6.112, 6.516, 6.502, 5.911,
6.069, 6.692, 7.081, 6.498, 5.976, 6.348, 6.311, 6.341, 5.381,
7.006, 5.965, 5.37, 5.652, 6.401, 6.82, 6.394, 6.207, 6.547,
5.016, 6.152, 5.456, 5.946, 6.595, 4.944, 6.151, 6.095, 5.714,
5.279, 5.83, 6.864, 5.711, 5.508, 7.248, 5.787, 6.396, 6.47,
4.872, 5.098, 6.271, 5.829, 6.88, 5.547, 5.769, 6.688, 5.786,
6.033, 6.425, 5.2, 6.2, 5.459, 6.834, 5.91, 5.718, 6.784,
6.603, 6.688, 5.405, 6.225, 6.74, 7.376, 5.74, 6.335, 5.935,
6.486, 6.772, 5.953, 5.135, 8.082, 5.81, 6.27, 5.372, 6.161,
5.642, 6.044, 6.19, 6.189, 5.193, 5.573, 6.394, 6.608, 5.954,
6.519, 5.845, 6.174, 5.795, 6.169, 5.288, 5.769, 6.364, 5.253,
6.865, 5.5), h_15 = c(7.454, 5.195, 5.94, 6.002, 10.864,
6.654, 6.799, 6.13, 5.498, 6.077, 6.352, 6.776, 6.88, 6.709,
5.871, 6.426, 6.077, 6.678, 6.65, 6.6, 4.99, 8.095, 5.381,
5.34, 5.845, 6.582, 7.072, 6.841, 5.417, 6.091, 7.357, 4.885,
6.02, 5.261, 4.931, 6.01, 5.036, 5.988, 8.589, 5.737, 7.698,
6.582, 5.255, 7.67, 5.562, 6.825, 5.761, 11.858, 5.826, 6.003,
6.589, 6.054, 6.282, 6.523, 6.136, 8.43, 6.082, 6.404, 6.26,
7.192, 6.736, 6.455, 6.068, 6.549, 6.964, 6.164, 5.568, 6.864,
6.019, 5.55, 5.904, 6.778, 7.021, 6.847, 6.406, 7.216, 5.114,
6.28, 5.775, 5.734, 6.615, 6.213, 6.276, 7.322, 6.023, 5.611,
5.306, 6.76, 5.528, 5.739, 7.329, 6.309, 7.257, 6.663, 5.473,
5.547, 6.534, 5.841, 6.962, 5.748, 5.743, 6.83, 5.843, 5.92,
6.964, 5.049, 6.489, 5.705, 6.73, 6.203, 5.531, 7.219, 6.125,
6.83, 5.7, 6.524, 7.36, 8.519, 5.953, 5.96, 6.946, 7.938,
6.982, 6.174, 5.345, 7.418, 6.511, 6.533, 5.5, 6.58, 6.061,
6.319, 6.395, 6.557, 5.7, 6.636, 6.572, 7.005, 6.473, 6.506,
6.007, 5.993, 6.241, 6.091, 5.691, 6.779, 6.31, 6.182, 7.12,
5.51), h_16 = c(7.353, 5.787, 6.161, 6.509, 11.262, 6.6,
6.672, 6.25, 5.535, 6.324, 6.301, 6.674, 6.839, 6.908, 6.514,
6.121, 5.723, 7.035, 6.788, 6.444, 5.472, 10.921, 5.469,
6.733, 6.099, 7.474, 7.784, 8.487, 6.129, 6.309, 8.839, 4.975,
6.244, 6.157, 5.251, 5.895, 5.091, 6.433, 7.946, 6.376, 8.058,
6.393, 5.201, 8.733, 5.122, 8.096, 5.822, 14.05, 6.429, 7.071,
6.739, 6.508, 9.411, 6.858, 6.112, 7.9, 5.593, 6.642, 6.337,
9.631, 6.39, 6.58, 6.185, 6.99, 7.174, 6.788, 6.501, 6.554,
6.3, 6.069, 6.71, 8.661, 7.087, 7.406, 6.401, 8.674, 5.231,
6.311, 6.501, 5.362, 6.612, 6.229, 6.31, 7.476, 6.371, 5.721,
5.987, 7.538, 5.516, 5.92, 6.986, 7.295, 7.904, 6.874, 5.512,
5.875, 6.642, 6.295, 7.16, 5.927, 5.687, 6.876, 5.897, 5.846,
6.982, 5.035, 6.525, 6.14, 6.65, 6.413, 5.853, 6.836, 6.103,
6.876, 7.094, 6.733, 7.558, 8.504, 6.279, 5.826, 7.607, 9.105,
6.933, 6.308, 5.709, 8.642, 7.368, 6.641, 5.486, 7.448, 6.471,
6.54, 6.284, 7.538, 5.985, 7.316, 6.634, 7.738, 7.202, 6.59,
6.25, 6.21, 7.009, 6.275, 6.944, 8.511, 6.414, 6.345, 8.462,
5.458), h_17 = c(7.167, 7.165, 5.919, 7.756, 12.506, 7.129,
7.412, 6.438, 5.298, 6.466, 6.854, 7.129, 7.202, 6.979, 6.77,
6.627, 6.324, 7.777, 7.203, 6.508, 5.667, 8.669, 6.065, 9.439,
7.285, 7.226, 8.281, 8.832, 6.582, 6.924, 8.522, 5.317, 6.729,
7.497, 6.009, 5.773, 5.262, 7.128, 7.873, 6.709, 8.085, 6.174,
5.836, 9.419, 4.893, 9.529, 5.867, 11.822, 6.705, 7.529,
8.222, 6.754, 9.434, 7.511, 6.234, 9.366, 5.612, 7.929, 6.565,
11.007, 6.612, 6.502, 5.569, 7.629, 7.499, 6.537, 8.403,
7.203, 7.194, 9.064, 7.337, 9.488, 7.423, 9.125, 6.571, 9.008,
5.25, 6.816, 7.807, 4.967, 7.059, 6.581, 6.776, 6.44, 7.372,
6.307, 7.067, 7.937, 6.697, 6.099, 6.541, 7.105, 7.735, 7.206,
6.397, 6.699, 6.785, 7.179, 6.538, 5.999, 5.715, 7.28, 5.899,
6.314, 7.874, 4.973, 6.749, 6.529, 7.329, 6.864, 6.686, 6.716,
6.861, 7.28, 7.058, 7.46, 7.692, 8.819, 6.566, 6.706, 7.498,
8.927, 7.233, 6.051, 5.679, 9.051, 8.124, 6.784, 6.083, 8.368,
6.798, 6.812, 6.552, 9.764, 6.555, 7.427, 6.784, 8.472, 9.907,
6.597, 6.547, 6.019, 7.633, 6.337, 7.115, 8.625, 6.184, 6.103,
8.772, 5.442), h_18 = c(7.058, 7.77, 5.969, 8.633, 12.037,
7.306, 6.894, 6.405, 5.153, 6.146, 7.364, 7.364, 6.957, 5.973,
7.169, 6.985, 6.725, 7.839, 6.587, 6.543, 5.967, 11.16, 6.889,
9.07, 8.09, 6.462, 7.865, 8.502, 7.144, 7.165, 8.531, 5.366,
6.528, 7.46, 6.469, 5.544, 5.238, 6.939, 6.006, 6.491, 7.755,
6.095, 5.895, 9.065, 4.411, 9.792, 5.774, 9.019, 6.529, 7.222,
7.882, 7.166, 10.153, 7.306, 6.164, 7.33, 5.754, 9.185, 6.489,
7.255, 5.806, 5.824, 6.048, 7.509, 7.557, 6.832, 9.135, 7.684,
7.419, 11.18, 7.139, 9.235, 7.238, 9.511, 6.481, 8.704, 5.364,
6.689, 8.963, 4.646, 6.716, 6.597, 6.789, 7.246, 7.212, 6.937,
7.719, 8.534, 9.163, 6.1, 5.794, 7.592, 7.438, 7.023, 6.806,
7.155, 6.878, 8.076, 6.093, 5.725, 5.875, 7.098, 5.715, 6.532,
8.449, 4.723, 6.721, 6.45, 6.776, 6.859, 7.236, 6.727, 7.348,
7.098, 7.021, 7.778, 6.834, 7.109, 6.399, 7.01, 7.898, 8.565,
6.871, 5.729, 5.585, 7.22, 8.55, 6.877, 6.558, 8.775, 6.949,
6.736, 6.673, 9.698, 7.03, 7.066, 6.649, 7.933, 9.846, 6.694,
6.554, 6.14, 7.51, 6.06, 6.983, 8.531, 5.996, 5.576, 7.289,
5.478), h_19 = c(5.687, 8.075, 5.892, 6.372, 10.094, 6.505,
6.055, 5.797, 4.308, 4.77, 6.675, 6.218, 5.605, 4.336, 6.558,
5.887, 5.707, 6.176, 5.783, 6.067, 5.872, 11.352, 6.618,
7.651, 7.454, 5.176, 6.72, 7.979, 6.034, 5.747, 8.054, 4.695,
4.984, 7.736, 6.157, 5.458, 5.261, 6.257, 3.821, 6.21, 6.625,
4.79, 5.316, 7.361, 4.711, 9.315, 5.403, 5.857, 5.525, 5.933,
6.151, 6.781, 4.937, 7.457, 5.419, 7.371, 5.079, 8.358, 6.193,
4.878, 5.904, 4.811, 6.298, 6.727, 7.392, 6.331, 6.913, 6.525,
6.486, 8.624, 6.014, 7.782, 5.672, 7.646, 5.664, 8.11, 5.042,
6.073, 8.246, 5.056, 5.858, 5.91, 5.882, 6.555, 6.22, 6.095,
7.354, 8.002, 4.622, 6.014, 5.29, 8.174, 5.627, 5.462, 6.43,
6.281, 6.237, 7.622, 4.942, 5.132, 5.341, 5.682, 5.091, 6.343,
8.041, 4.818, 6.213, 5.921, 5.557, 6.2, 7.53, 6.659, 6.437,
5.682, 6.235, 7.109, 5.464, 4.284, 5.601, 6.94, 8.228, 9.3,
5.611, 5.032, 5.403, 7.09, 6.221, 6.236, 5.1, 8.594, 6.678,
6.037, 5.728, 7.849, 5.225, 4.217, 5.536, 6.219, 7.906, 6.242,
5.73, 5.873, 6.65, 5.933, 6.499, 8.912, 6.167, 5.503, 4.775,
5.145), h_20 = c(4.335, 7.319, 5.038, 3.809, 7.279, 5.174,
4.37, 4.575, 4.01, 2.962, 4.964, 4.469, 4.154, 2.597, 5.11,
4.389, 4.196, 4.113, 4.463, 4.879, 4.825, 6.801, 4.192, 6.711,
5.633, 3.724, 4.825, 5.548, 5.191, 3.998, 4.551, 3.612, 3.448,
7.235, 5.353, 4.955, 4.804, 5.121, 2.528, 5.686, 4.958, 3.28,
4.306, 4.993, 4.507, 6.502, 4.176, 4.384, 4.169, 5.125, 4.224,
5.82, 2.643, 5.897, 4.583, 3.95, 4.013, 5.609, 5.064, 3.315,
4.745, 3.624, 4.79, 4.735, 5.903, 5.266, 4.293, 4.887, 4.835,
4.672, 4.213, 4.997, 3.919, 5.129, 4.28, 5.412, 4.299, 4.906,
5.149, 4.539, 4.291, 5.092, 4.387, 4.581, 4.551, 5.163, 6.564,
6.223, 3.045, 5.073, 3.796, 5.932, 3.251, 3.328, 5.627, 4.159,
4.307, 5.604, 3.305, 4.146, 3.588, 3.425, 4.128, 5.207, 5.942,
5.47, 4.795, 4.636, 3.923, 5.068, 7.024, 5.559, 4.797, 3.425,
4.749, 5.418, 3.967, 2.817, 4.05, 4.93, 6.056, 5.937, 3.952,
4.567, 4.945, 4.655, 3.797, 4.306, 3.789, 5.892, 5.141, 4.769,
4.452, 4.943, 3.388, 2.495, 3.919, 4.386, 5.201, 4.942, 4.51,
4.579, 4.658, 5.084, 5.059, 6.827, 5.386, 4.819, 3.15, 4.386
), h_21 = c(3.86, 3.419, 4.111, 2.631, 2.901, 3.924, 3.444,
3.567, 3.663, 2.51, 3.592, 3.19, 3.056, 1.699, 3.313, 3.106,
2.53, 4.047, 2.854, 3.757, 3.214, 5.125, 3.464, 3.532, 4.447,
2.206, 3.573, 4.029, 3.56, 2.206, 3.041, 3.331, 3.154, 3.713,
2.721, 3.886, 3.941, 4.302, 1.914, 3.58, 3.578, 2.488, 3.295,
3.419, 3.464, 4.121, 3.959, 2.623, 3.114, 3.845, 2.729, 3.271,
2.364, 4.42, 3.901, 2.958, 3.419, 3.846, 3.942, 2.502, 3.382,
2.949, 2.888, 3.22, 3.898, 3.666, 2.721, 3.333, 3.232, 3.074,
2.769, 3.477, 2.933, 3.637, 3.498, 3.93, 4.048, 4.086, 2.949,
3.302, 3.14, 2.861, 3.726, 3.719, 3.748, 3.726, 2.921, 4.167,
2.42, 3.438, 2.806, 4.92, 2.626, 3.024, 3.408, 2.507, 3.624,
2.182, 2.355, 4.125, 2.99, 2.472, 4.123, 4.021, 3.955, 4.36,
3.393, 3.194, 2.623, 4.183, 4.177, 4.048, 3.315, 2.472, 3.006,
4.156, 2.923, 2.275, 3.577, 3.417, 4.577, 4.397, 2.805, 3.977,
3.541, 3.47, 2.691, 3.623, 3.066, 3.351, 2.95, 3.814, 3.464,
3.415, 2.565, 1.514, 4.005, 3.375, 3.57, 3.788, 4.596, 2.815,
2.734, 3.424, 3.232, 5.065, 4.094, 4.471, 2.373, 4.404),
h_22 = c(3.696, 2.023, 3.479, 2.055, 2.163, 3.123, 2.472,
2.54, 3.189, 2.453, 2.989, 2.69, 2.246, 1.216, 3.239, 2.623,
1.928, 4.207, 2.124, 2.968, 3.213, 3.784, 2.654, 2.123, 3.304,
2.814, 2.691, 3.423, 2.341, 1.337, 2.192, 3.08, 3.232, 2.579,
1.511, 3.344, 4.409, 4.034, 1.686, 2.237, 2.774, 2.157, 2.773,
2.464, 3.446, 2.751, 3.929, 2.048, 2.612, 3.692, 2.106, 1.589,
2.063, 3.477, 3.512, 2.851, 3.059, 3.226, 3.348, 2.064, 3.048,
2.397, 2.743, 2.451, 2.823, 2.567, 2.173, 2.458, 2.375, 2.476,
2.321, 2.831, 2.438, 2.611, 3.325, 3.481, 4.156, 3.557, 2.092,
4.33, 2.636, 1.537, 3.45, 2.511, 3.678, 2.096, 1.851, 3.461,
2.603, 3.488, 2.362, 3.282, 2.314, 3.142, 1.986, 1.642, 3.632,
1.055, 2.153, 4.491, 2.856, 2.397, 4.122, 3.356, 2.934, 4.786,
2.589, 3.187, 2.048, 4.002, 2.735, 2.987, 2.698, 2.397, 2.828,
3.752, 2.097, 2.043, 3.777, 2.9, 2.703, 2.717, 2.257, 3.32,
3.618, 2.996, 2.167, 3.632, 2.673, 2.361, 2.528, 3.243, 2.883,
2.632, 1.963, 1.051, 4.194, 2.675, 2.631, 2.803, 4.846, 2.025,
2.77, 2.626, 2.987, 3.567, 3.198, 3.879, 1.992, 4.539), h_23 = c(2.771,
1.806, 3.231, 1.822, 0.874, 3.096, 1.884, 2.118, 3.401, 1.712,
2.575, 2.425, 1.7, 0.833, 3.21, 2.331, 1.635, 3.212, 1.81,
2.477, 2.83, 3.832, 2.955, 2.364, 3.092, 3.731, 2.257, 2.996,
2.081, 1.062, 1.65, 2.328, 2.478, 2.521, 1.246, 3.046, 4.689,
3.862, 1.118, 1.894, 2.37, 1.515, 2.688, 2.22, 3.068, 2.166,
3.274, 1.653, 2.135, 2.91, 1.881, 1.311, 1.53, 2.917, 3.262,
1.914, 2.184, 3.067, 2.963, 1.126, 2.437, 1.724, 2.374, 2.059,
2.302, 1.865, 1.824, 2.203, 1.893, 2.236, 2.286, 2.196, 1.89,
2.371, 2.525, 3.207, 3.87, 3.359, 1.699, 4.334, 1.992, 1.304,
3.103, 2.454, 3.464, 1.819, 1.758, 3.134, 2.076, 3.827, 1.898,
3.213, 1.611, 2.344, 1.466, 1.318, 2.943, 0.808, 1.592, 3.638,
2.408, 1.957, 3.311, 2.834, 2.711, 5.069, 1.998, 3.226, 1.703,
3.527, 2.505, 2.487, 2.322, 1.957, 3.006, 3.355, 1.529, 1.497,
2.97, 2.723, 2.029, 2.036, 1.741, 2.5, 4.043, 2.586, 1.534,
2.942, 2.556, 1.832, 2.586, 2.321, 2.488, 2.472, 2.027, 0.891,
3.262, 2.081, 2.582, 2.053, 3.648, 1.831, 2.555, 2.312, 3.148,
2.915, 2.893, 3.55, 0.353, 3.713), h_24 = c(1.516, 1.248,
1.984, 0.918, 0.314, 2.254, 1.036, 1.374, 1.011, 1, 1.993,
1.617, 1.244, 0.555, 2.287, 1.777, 1.033, 1.891, 1.031, 1.717,
2.167, 2.443, 1.655, 1.944, 2.202, 3.513, 1.457, 1.779, 1.281,
0.745, 0.987, 1.579, 1.433, 1.748, 0.825, 2.249, 4.116, 3.06,
0.679, 1.393, 1.779, 0.978, 2.229, 1.602, 1.854, 1.215, 2.428,
0.503, 1.557, 1.299, 1.148, 0.801, 0.487, 1.878, 2.732, 0.652,
1.45, 2.161, 2.309, 0.313, 1.683, 1.293, 1.692, 1.547, 1.174,
1.252, 1.102, 1.525, 1.292, 1.338, 1.234, 1.309, 1.27, 1.452,
1.584, 1.97, 3.122, 2.457, 1.055, 2.882, 1.158, 0.83, 2.086,
1.878, 2.694, 1.223, 1.133, 1.786, 1.089, 3.285, 1.131, 2.242,
1.025, 1.362, 0.956, 0.597, 2.006, 0.465, 1.102, 2.474, 1.779,
1.363, 2.129, 2.214, 1.95, 4.824, 1.127, 2.634, 1.07, 2.754,
1.954, 1.576, 1.76, 1.363, 2.411, 2.436, 1.027, 0.843, 1.989,
2.183, 1.383, 1.187, 1.211, 1.204, 3.67, 1.271, 0.774, 2.006,
1.825, 1.212, 1.921, 1.468, 1.728, 1.623, 1.678, 0.444, 2.039,
1.32, 1.767, 1.336, 2.22, 1.008, 1.943, 1.45, 2.728, 2.065,
1.78, 2.981, 0.24, 2.61)), class = "data.frame", row.names = c(NA,
-150L))
Комментарии:
1. вы можете использовать либо иерархическую кластеризацию (разрежьте дерево так, чтобы у вас было 15 типов), либо кластеризацию k-средних (необходимо заранее указать количество типов), среди различных вариантов.
2. @desval спасибо за совет. Возможна ли иерархическая кластеризация для такого набора данных, который имеет не только два измерения, но в основном 24?
3. конечно, вы можете иметь их столько, сколько захотите. Масштабирование учитывает тот факт, что эти переменные могут иметь разные величины.
Ответ №1:
Существуют разные способы достижения этого. В общем, вы ищете какой-то неконтролируемый метод обучения (имеете некоторые немаркированные данные с характеристиками и хотите группировать наблюдения (дороги) на основе сходства)
Сначала обратите внимание, что в ваших данных тип включает дубликаты. Этого не должно быть, если каждый ряд — это отдельная улица. Я предполагаю, что это ошибка:
d$type <- paste0("id_", 1:nrow(d))
dd <- as.matrix(d[,-1])
rownames(dd) <- d$type
K-означает кластеризацию:
dd <- scale(dd)
# 4 means clusering
set.seed(123)
km.res <- kmeans(dd, 15, nstart = 25)
# get cluster membership
km.res$cluster[1:10]
id_1 id_2 id_3 id_4 id_5 id_6 id_7 id_8 id_9 id_10
3 10 3 6 2 9 3 3 12 15
Альтернативно, иерархическая кластеризация:
# hierarchical clustering
dist_mat <- dist(dd, method = 'euclidean')
hclust_avg <- hclust(dist_mat, method = 'average')
plot(hclust_avg)
cut_avg <- cutree(hclust_avg, k = 15)
plot(hclust_avg)
rect.hclust(hclust_avg , k = 15, border = 2:6)
abline(h = 3, col = 'red')
# get cluster membership:
cut_avg[1:10]
id_1 id_2 id_3 id_4 id_5 id_6 id_7 id_8 id_9 id_10
1 2 3 3 4 3 3 3 5 3
Обратите внимание, что в целом разные методы будут иметь разные результаты. Если вы заглянете в файлы справки функций, вы найдете больше информации о возможных вариантах для каждого метода, например, для определения расстояния и о том, как вычислять кластеры (среднее, максимальное, минимальное, уорд).
Комментарии:
1. Большое вам спасибо! Это
ablineтолько по эстетическим соображениям, чтобы указать, где вы разрезаете дерево на ветви?2. да, в идеале это должно быть на уровне, который приводит к выбранному количеству классов. 3 — это просто «случайное» число.